"Closing the Loop" - Customer Feedback Management

8 Key Insights about CX and Text Analytics

2017-04-27T09:43:00.001-04:00

Today I shamelessly re-blog a post from my friend and colleague - Matti Airas from Etuma. The post in its entirety can be found here:

Matti's Blog post on Etuma.com should be required reading for anyone looking to implement a customer feedback process, a customer experience management process, or text analysis process. He makes 8 key points that discuss why and when organizations can benefit from CX / Text Analysis technology. And also, when they maybe can't or shouldn't take on CX. The Title of his post is:

What I learned from 159 CX Text Analysis Projects

Matti participated in a large number of text analysis projects - Companies bringing datasets into the Etuma text analysis system. I have been involved personally in some of them. So, I know what he is speaking about. And, the truth in his words. I highly recommend reading it.

So, without further ado, here's the text of Matti's post:

1. Every single dataset has insights in it

In these 159 datasets I have still to find one that doesn't have some operational or strategic value. I have to admit that sometimes the value is anecdotal–finding minor operational issues and getting product/process improvement ideas–and that it is difficult to calculate a solid ROI for CX text analysis investment (I mean, what is the value of better information?!).

The key is continuous feedback: B-to-C companies with solid NPS survey process in place for over a year, can always extract both strategic and operational insights out of customers' unstructured feedback. And reversely, without a solid feedback process, the benefits for analyzing customer feedback are limited. Good data is paramount!

2. Net Promoter System is the main driver for CX text analysis

Net Promoter System drives CX text analysis demand but especially during the past year, with the need to retain great employees increasing, and the emergence of eNPS we've seen lot more demand for employee experience analysis.

Contact center complaint analysis is also becoming more important. The process, which made sense in a world in which complaints came via phone, might not work for electronic feedback. When complaints are coming in via Tweets, FB postings, emails and webforms, it is evermore difficult and expensive to manually categorize them. Semantic social media analysis has been talked about for many years but we are yet to see great demand for it.

3. Most companies struggle with text analysis

There are plenty of tools to analyze structured data but unstructured data analysis is still a relatively new industry. This combined with the lack of competent text analytics people leads companies to struggle with on how to solve the text analysis problem.
I wrote a white paper called CX Professionals Guide to Text Analysis. It helps you find the right method and tool for your CX and EX text analysis needs and requirements.

4. The reason not to buy is not text analysis quality

I remember only two or three cases in which the reason not to buy was text analysis quality. Most CX and EX text analysis solutions categorize feedback accurately and sentiment analysis works way beyond any statistical relevance requirements. The reason not to buy boils down to these three issues:

Lack of top management commitment: no CX strategy (=>no budget, no resources);
Insufficient or bad feedback gathering system (=low volume or bad quality); or
Not having the right people and competencies for CX analytics.

Two or three years ago the main issue used to be the feedback volume/quality and before that the lack of top management commitment. Now the top issue is lack of analytics competence.

5. Extracting insights is difficult

Even if every single feedback dataset has actionable insights, it doesn't mean that extracting insights is easy. Developing the right competencies in order to turn the analysis results into actionable insights seems to be a challenge.
Most companies, even large enterprises, don't have enough time and resources to develop niche horizontal competencies. Customer and employee experience analytics is one of these niche horizontal competencies. The learning curve is quite steep. It takes months of full time effort, background knowledge in statistics, and experience in visualization and analytics tools to be able to effectively extract insights. And even if one person has become good at it, they either move to a new position or change employers.
Customer experience analysis results are like any other data: actionable insights don’t jump out and announce their existence and importance. Actually, CX analytics is even harder because most of the feedback is text and it is unstructured. CX analysis results are raw material that you have to enrich and refine. That's why you need to implement a CX analytics process.

I wrote a white paper called CX Professionals Guide to Extracting Insights to assist in solving this problem. Follow this process and you will be extracting actionable insights and sharing them with CX and EX stakeholders in weeks.

6. Many companies have bigger problems

I've heard potential customers, even many who receive lot of feedback, say that even if they knew what is wrong with customer experience, they wouldn't be able to close the loop: for cultural, technological or organizational reasons they just wouldn't be able improve or change anything. That is a sad and cynical attitude. In these cases analyzing feedback makes no sense. These organizations have bigger problems.

7. CX text analysis is sticky

Once you start using a CX text analysis service, you cannot get rid of it. The only thing you can do is change vendors but getting rid of it isn't an option. Once correctly implemented combined with sufficient analytics competence, CX text analysis brings concrete business benefits. And, nobody wants to go back to reading and tagging comments manually.

8. Customer centricity has the power to transform organizations

Once you have the customer experience management process in place and the front-line employees have been indoctrinated with customer-centric thinking and you have implemented the correct support processes, such as Service Recovery Process, customer experience delivery people will know instinctively how to react even in unusual situations without having to ask their supervisors for advice and permission. This improves customer experience, motivates employees and makes organizations more efficient. When implemented right CX analytics has the power to transform organizations!

Use Text Analysis and Dashboards together!

2017-03-02T10:01:00.002-05:00

Text / Comment / Verbatim analysis is a fantastic technology for understanding customer experience.

Customer comments, whatever their source, contain lots of very useful information. They tell businesses about challenges and opportunities, frustrations and delights, poor processes and great. In fact text analysis systems are so effective now-a-days that their main challenge in the market is providing enough visualization capability so that their analysis results can be presented easily. And thereby, informing managements about actions they should be taking in response to the feedback that they are getting.

Visualization tools do a great job helping businesses drill down on complex data sets, then extract and present relevant salient facts in easy to understand visualizations.

Text analysis provides the complex data sets, placing statistically valid structure around unstructured data (text and comments), in the form of topics discussed and sentiments expressed. Visualization tools drill down on that newly structured data and make it actionable.

Visualization and Text Analysis should be used together. At Etuma we understand this. We provide some of our own visualizations. But, importantly we have built in connectors to visualization systems that provide real-time data flow to dashboards built with them. Some examples of visualizations that can be built off of Etuma created data sets can be found in this excellent post on the Etuma Blog: 12 Text Analysis Visualization Tips. I encourage you to check them out.

Stewart Nash
GM Etuma USA
stewart@etuma.com

Smart Loop Closing with Text Analysis

2017-02-21T13:22:00.003-05:00

I subscribe to Bruce Temkin's Customer Experience Matters blog. Its a good resource for folks who are "doing" customer experience. In a recent a post and report titled: "Use Customer Insight To Close Four Loops" Temkin made the argument that there are four distinct feedback loops that organizations need to evaluate and act on. As a proponent of Closed-Loop feedback management I am very much in agreement with Temkin's four feedback loops and approaches for "Closing" those loops. The Temkin article can be read here. He uses restaurant chain feedback as an example.

Text Analysis can contribute to implementing loop-closing processes for each of Temkin's four loops. The four feedback loops include:

Immediate Response
Corrective Action
Continuous Improvement
Strategic Change

Immediate Response. Temkin - Rreach out to a restaurant customer who responded on a survey that "the bathroom was dirty" and help take care of her ongoing concerns.

How Text Analysis can help.

In the immediate response scenario, feedback from customers of this type is typically delivered directly to the store manager, who then responses to the person providing the feedback or acts on solving the problem. Text Analytics only provides limited help in this instance documenting the issues a customer or customers are having.

Corrective Action. Temkin -Get the manager or employee to clean the bathroom in that restaurant.

How Text Analysis can help.

Though immediate corrective actions are likely being spawned by the immediate response process handled by store managers, taking broader corrective actions that prevent issues from re-occurring is something Text Analytics is very good at helping with. For instance, if dirty bathroom is a regular occurrence at a particular restaurant or group of restaurants then there may be a training, process or staffing issue that higher level management needs to address. Text Analysis can also help understand what "dirty" actually means. i.e. is it full trash cans, dirty floors, dirty stalls, etc.. Text Analysis can often pinpoint what the most severe issue actually is, making it a lot easier for senior management to provide specific guidance to store managers on corrective actions to take.

Continuous Improvement. Temkin - Create new process for restaurants to check and clean bathrooms on a regular basis.

How Text Analysis can help.

Similar to corrective actions, Text Analysis can help a lot with continuous improvement efforts, by continuously monitoring and reporting changes in topic sentiment about various aspects of, in this case, bathrooms, Soap dispensers , hand dryers, cleanliness of sinks, floors and toilets. All these topics that can be monitored for changes in sentiment (and using Etuma, can be filtered by region, district or restaurant as well) , enabling proactive management of "dirty" bathroom issues across the restaurant chain.

Strategic Change. Temkin - As part of new restaurant formats, design bathrooms so that they don’t require as much time from employees to keep them clean.

How Text Analysis can help.

Here again, Text Analysis can be very helpful in the strategic domain, by providing insight about what "dirty" actually means for customers, which in turn informs how to strategically change for the better. For instance, if "dirty" often means un-flushed toilets, a strategic change could be to install self-flushing toilets in the restaurants.

Temkin's bottom line: Make sure to build out four closed loops.

My point: using Text Analysis makes it a lot easier to determine which actions to take to "Close" each loop. Also, actions taken will be supported by data, as text analysis is providing statistically meaningful support for the insights being generated. The result being that its much more likely that customer issues will actually be addressed in such a way as to improve VOC.

A couple of additional points....

Automated Text Analysis provides continuous and on-going evaluation of feedback. When people have to do the evaluation of feedback without text analysis, they can be inconsistent, or if there is lots of feedback, only base their analysis on samples. So, for organizations who want continuous improvement, continuous monitoring is necessary.

Changes in topic sentiment are difficult for people to identify unless the change is dramatic. Automated Text Analysis solutions (such as Etuma) are able to assess and document changes to topic sentiment over short periods of time based on changes in the relative volumes of topics discussed in received feedback.

So, by all means, close Temkin's four feedback loops. But, by using automated Text Analysis, closing loops will be quicker, smarter and less effort than otherwise.

Etuma's 5 rules (and some comments) for creating a powerful customer feedback gathering system

2017-01-03T17:32:00.001-05:00

My colleague - Matti Airas - published this on Etuma's Blog (Click Here to read the original). I liked the thrust of the post. So, I thought I'd re-post it here and add my own commentary to it. So full credit to Matti and Etuma on this. My comments in Red.

At Etuma, we have analyzed hundreds of different feedback processes and formats and seen what works and what doesn’t work. For a feedback analysis company, we have become surprisingly expert in the process of gathering feedback. We have learned how to design a survey process that both maximizes the volume of open-ended feedback and provides concrete actionable insights.

1. Make it easy and ubiquitous to submit spontaneous feedback

Give customers the possibility to choose the channel they prefer. This includes text messaging, web forms, twitter, Facebook and email. Remember, the customer chooses the feedback channel, not you. Put the feedback URL everywhere. Don't be afraid to receive feedback, embrace it! Needless to say, I agree with all of this. But, I feel its particularly important to trigger "outbound" feedback gathering at key touch points, even if there is not a transaction involved. As a personalized appeal to provide feedback is more effective than a feedback link customers glance at in passing.

2. Run transaction-based surveys for key touchpoints

We like the transactional Net Promoter Score system (TNPS) but it can be any format as long as it is short and relevant for the experience (touch point) you are tracking. In transactional surveys the two most important things are timing and brevity: conduct the survey soon after the event using sms or email, and keep the survey as short as possible. Remember that NPS is not suitable for every transaction. For example, in customer support context, the Customer Effort Score (CES) is a better format. Again, I'm in complete agreement with this approach. Having an e-mail or text based process as your feedback gathering core is important as it allows personalized and follow-up-able feedback to be gathered.

3. Dig deeper when you don’t have enough information

Customer experience management (CEM) platforms enable you to run sophisticated rule-based surveys. You should use this functionality to find out e.g. why people stopped using a certain product or when their survey response didn’t explain the reason for their reaction (e.g. NPS score) or provide sufficient information for root-cause analysis. Amen to this. There are multiple ways to approach the need for additional "drill down" data. One is through rules based design. Another approach is to send follow-up surveys that incorporate original survey responses plus additional background data from your databases.

4. Run periodic relationship surveys on a representative sample

Spontaneous and touch point specific surveys often fail to get a comprehensive view on brand, competitor, pricing and marketing related issues. It is important to keep the relationship survey format as similar as possible to the transaction survey (although the periodic survey can have more questions). This gives you the ability to analyze customer feedback as a whole across all channels. Unless you have really large numbers of customers, say over 100K, today's feedback management systems make it easy to survey all your customers whenever you need to (typically 2x per year for relationship surveys).

5. Connect your company’s and competitors' Facebook pages and Twitter handles to the analysis service

More and more of the brand, product and service discussion is moving into social media. You need to connect your main social media channels into the feedback analytics process. Again, Amen to this. But, these channels are often not given the kind of serious attention that other processes are given. Gathering feedback from social media is important. Tying this type feedback into all the other feedback is critical.

6. My personal most important Rule about feedback gathering. Never ask a customer to give you information via feedback which you already possess (and which they know you possess).

Nothing turns off a customer faster than a survey seeking redundant information.

Don’t try to get an answer to every question in one survey. Create a continuous high-volume communication process, in which the complete picture is formed from many small fragments. This is the best advice of all.

Follow up Boosts Survey Response Rates

2016-12-02T14:43:00.002-05:00

This is a topic I've written about several times over the last 3-4 years. It's been my contention that response
rates for customer surveys are much higher when there is an expectation of follow-up action on the part of the company issuing the survey.

Clearly, there are ways to boost survey response rates that don't include follow-up. Survey length, survey design, number of reminders and availability of mobile device support all effect response rates. But, in my experience doing customer surveys, about the best response rate that can be expected for customer survey processes not employing direct follow-up is 25%. In other words, if a business surveying customers does everything else right and doesn't follow up, 25% is a reasonable expectation for maximum response. Though, I expect few businesses attain that level of response rate very often on their survey processes.

In my experience, for businesses employing customer survey processes where follow-up is included, the maximum response level can be much higher than 25%. I've worked with businesses for several years implementing customer survey processes built around follow-up. What I have seen is response rates that tend to rise over time (versus declining over time as is generally the norm in surveying). And, I routinely see response rates above 40%, with some even above 50%.

For me, the evidence is in that expectations for follow-up on the part of customers drives response rates higher over time. It would seem obvious that this would be the case. But, most businesses in my experience aren't likely to act on feedback often enough to give their customers this expectation.

The chart below shows response rates from one of my clients who I've conducted eight surveys for over the last five years. All the surveys used an NPS approach, employed what I've described above as "good" design practices and included multiple reminders plus follow up. Follow-up was facilitated by the "Notifications" process embedded within the QuestBack Essentials platform I use to deliver the surveys (meaning that follow-up is triggered by response profile). You'll see the early surveys tended to have lower response rates and the later surveys higher response rates.

Two things have been going on with this particular client. First, customers have developed the expectation that their feedback is going to be followed-up. Second, the business has actually implemented follow-up processes and responds to people giving feedback. If you notice, in the early surveys, customers did not have the expectation of follow up (they had not yet developed it). And, frankly the business really wasn't all that committed to following-up, at least at first. But, between survey 3 and Survey 4 this client began to have lots more competition. They reacted by paying a lot more attention to survey responses, acting on them individually and thereby improving customer experience across the business.

Beyond higher response rates, this business has improved customer retention, overall profitability and survived the entrance of major competition into its local market. And, in many ways has become a stronger competitor by paying attention to customer experience through the survey feedback / follow up process.

A last note. In this customers current survey process, response rate is at 53% and still rising.

- Stewart Nash
LinkedIn: www.linkedin.com/in/stewartnash

Verbatim Analysis - A crucial technology to use in business

2016-11-29T13:58:00.001-05:00

My friends at Etuma recently put out a post titled "9 Reasons why you shouldn't wait to implement a verbatim analysis solution. Click Here to read the blog post in its entirety. I liked the article enough that I thought I should reiterate the points and expound upon the underlying needs for actionable data that companies today have. Summarizing the Etuma post:

1. Leading companies in many industries have well developed customer listening skills. Most customer listening remains survey driven, but increasingly it is becoming omni-channel (meaning surveys plus social media) are quite well. Your competitors are learning and transforming how they react to the customer's voice. Your company needs to as well.

2. Customer needs are becoming harder to predict. You need to have data that can feed analytical and predictive analysis tools in order to more rapidly detect emerging trends. Verbatim feedback is one of the data sources predictive analysis relies upon.

3. Paying people to decipher and report on customer interactions provides expensive and inconsistent data.
Feedback enters the call center from phone, emails, web forms and chat logs. Once calls are transcribed it's all unstructured open-text data and can be fed to verbatim analysis systems.

4. Front-line staff turnover is often quite high in contact centers - compounding the issues in #3 above by requiring constant training and monitoring to provide some consistency of results.

5. Many companies do not get customer feedback directly. As most of their products are sold indirectly, feedback is only as good as the filtering mechanisms that exist in their distribution networks. i.e. It is usually not good. Verbatim feedback lets product vendors monitor 3rd party review or web sites and detect issues and trends without feedback being filtered by the distribution network.

6. New products and services are introduced constantly. Detecting the presence of a new product or its impact on existing offerings is a lot easier when that information is extracted from customer comment automatically.

7. Just like new products, new competitors are much easier to detect when data sources are being analyzed and regularly.

8. Omni-channel marketing and sales makes the customer journey complex. Shopping has become more complicated. The customer journey can now involve many interactions with the company. Capturing those interactions and understanding them consistently and quickly is important and much easier with automated verbatim analysis.

9. Social media complicates communications and crisis management. Getting quicker understanding of issues makes reacting to them a lot easier and the reactions can be much better planned.

Etuma makes the general point in the post that topic / issue detection and sentiment change detection are critical capabilities for organizations to have these days. And, especially so where a company doesn't get direct access to feedback. The point I would make about the urgency of implementing text analysis capabilities is the "Don't know what you don't know" factor. Meaning that without tools to detect issues and sentiment changes (Things you don't know), businesses Don't know What they Don't know.

In today's world, not knowing something important for any length of time tends to have associated costs. By the time a business learns what it needs to know about something, it may be too late to fix a problem, create a new product, add a new service or otherwise react to customer needs in effective ways.

The urgency of adopting automated text analysis solutions is clearly high. Hopefully more businesses will do so sooner rather than later.

No Text Analysis = No Voice of the Customer

2016-08-02T10:34:00.000-04:00

A bit of a provocative title to this post. That said....

Having been part of the customer survey business for a number of years, I believed that quantitative customer surveys, and analyses of survey data, could provide a reasonable approximation of the customer's "voice". In particular Net Promoter Surveys did a good job of that. Over time, my opinion on the subject has changed, to the point where I think that quantitative customer surveys cannot any longer be exclusively relied on to approximate the "voice of the customer" (VOC). In my opinion there are two reasons why quantitative approaches don't work as well as they did: The necessity of concise surveys and the increase in alternative non-quantitative channels being used by customers to provide feedback.

"Back in the day", when customers could be relied on to complete questionnaires with fairly large numbers of questions and would do so in numbers large enough to give a reasonable sample, surveys could in fact approximate VOC. Today though, customer surveys have to be VERY concise in order to generate reasonable response rates, and verbatim questions have to be substituted for the questions we used to, but cannot any longer, ask. Customer surveys have become so concise that many businesses today use surveys with a single question and a single verbatim option. With such short surveys I don't think its possible to approximate VOC unless some sort of text analysis is being applied to the verbatim responses being received.

Additionally, social media has been adopted by many businesses (particularly in retail) as a channel for customer interaction. Here again, verbatim comments are the mechanism being used to provide opinions, make complaints, suggest changes, share experiences, etc.. Without using text analysis there's no easy way to aggregate and understand what they are talking about, which topics are trending, which are positive and which are negative.

Needless to say, for people in the VOC space, none of what I'm saying is a revelation. In fact, text analytics has been around for a while now. Customer surveys are shorter today and rely on more verbatim responses than ever before. Survey response rates are generally lower across the board than they've been in the past. All the conditions exist for a sea change in how businesses ascertain VOC. So, to me, its clear that Text Analysis is something more and more businesses will need to adopt going forward.

For large businesses, with the necessary resources, implementing a combined social media, customer survey and text analytics based VOC process isn't difficult. It costs a lot of money, but ROI is good given the scale of their needs. Smaller businesses though have to consider lower cost and easier-to-implement approaches. Fortunately those exist, often as component based multi-vendor solutions. The key in these situations is easy-to-implement APIs so that customer feedback can flow through various channels into the text analysis tool and then on to customer dashboards or other visualization environments, as needed.

Voice of the Customer today without text analysis isn't representing the customer's voice very well. But, Text Analysis is getting easier to do and lower in cost all the time. Businesses that do not today use Text Analysis in their VOC process should consider doing so.

- Stewart Nash (www.linkedin.com/in/stewartnash)

4 Reasons to try Etuma Text Analysis

2016-05-19T11:04:00.001-04:00

Its been a while now since I last posted on Etuma's value proposition. Needless to say, since that time the folks at Etuma have done boatloads of product enhancements. Though I've always felt Etuma offered huge value to American businesses, I am more convinced today than ever before of its value proposition. For companies doing business in the Americas, Europe and other places where European languages prevail, Etuma can provide insights, enable better decision making and reduce the costs of customer experience analysis.

4 Reasons Etuma Text Analysis is really good for your business....

Reason #1. - Most importantly, Etuma shows you what your customers are talking about, as well as how they feel about each topic. In today's world of text analytics - euphemistically - this is table stakes. But, Etuma "antes up", with multiple "Viewpoints" (industry and function categorization models) and automated topic / sentiment analysis. For those who don't know, doing both topic and sentiment analysis together offers unique value because it helps pinpoint areas where problems exist, opportunities present or change is occurring. Etuma's analytics allow views based on daily, weekly, monthly, quarterly or annual changes in topic sentiment across entire sets of verbatim comments, or for any filtered subset of the data.

Reason #2. Etuma is very user friendly. It doesn't require data scientists, data analysts, or other expensive experts to use the product in order to produce hugely valuable insights for your business. Once you feed data into Etuma, you can start analyzing results. This makes Etuma extremely cost effective from an operational standpoint. You don't need expensive consultants in order to create and use verbatim insights. Needless to say, this ability to avoid $200 per hour consultants saves money.

Reason #3. Etuma's Dashboard-like presentation of feedback results let you share and act on insights rapidly and easily. For more in-depth analyses Etuma's connectors to Tableau and other Dashboard systems lets you easily incorporate all your verbatim feedback into your business analyses. But, once data is in Etuma, any report you create is shareable out to dozens of colleagues simply by assigning them access to it. Reports, once set up, automatically update as new feedback comes into the system. Again, operationally, Etuma saves you lots of money because your reports don't have to be manipulated by data experts in order to provide value to colleagues.

#4. Etuma is multi-language out-of-the-box. ZERO additional effort is required to have Etuma analyze verbatim feedback in any of 10 European languages. It reports results in any of the 10 languages it supports. So, if your CX team has people in Germany, France, US, Spain, etc., each can see their reports in local language, even though feedback came through in any of the other nine languages. Any comment, in any analysis can be immediately translated to local language at the click of a button. Etuma's Language support is enormously cost effective as it facilitates collaboration among CX staff in multiple countries and virtually eliminates the need for translation services for CX analysis.

Etuma is a low cost solution. Our customers typically pay well under 1 cent per verbatim comment analyzed.

Etuma's Value Proposition - High quality topic / sentiment analysis in a user friendly package offering an operationally efficient implementation with low requirements for data or language experts. All in a low cost product.

Lastly and best of all, Etuma offers a free trial. You load some data then start analyzing. Its that simple. If you'd like to try Etuma. Just contact me.

Stewart Nash
Etuma USA
stewart@etuma.com
LinkedIn: www.linkedin.com/in/stewartnash

Mobile / On-line delivery optimizes Transactional survey response

2016-05-03T09:31:00.000-04:00

I've been working on Transactional surveys with a new QuestBack customer for the last couple of months where our QuestBack is replacing another vendor's product. What' been very encouraging is the response rate improvements QuestBack mobile adaptive surveys are receiving. The surveys we've implemented thus far are receiving substantially greater response rates. The difference, in my opinion is "device adaptive" survey forms.

Device adaptive simply means that QuestBack surveys present equally well on mobile, tablet or standard laptop / desktop devices. Obviously, this allows respondents to respond from wherever they happen to be when they receive an invitation. It has absolutely increased response rates for the client.

How much better are QuestBack's device adaptive surveys? Transactional surveys often receive lower response rates, 8-10% being typical. Mobile only survey companies discuss "mid-teens" response rates as being high. On one survey using QuestBack, the customer is receiving over 20% response versus ~12% before. On another they are approaching 30% versus 25% before.

QuestBack's device adaptive, multi-channel and closed-loop follow up supported surveys produce high response rates and provide detailed insights about customers. In fact, one client I do surveys for using QuestBack is receiving a nearly 50% response rate on a relationship survey delivered via e-mail. I've discussed this phenomenon in other posts before (see http://close-the-loop.blogspot.com/2015/06/mobile-support-increases-survey.html for more information). But, wanted to point out that device adaptability can have a powerful effect on transactional survey response rates too.

Stewart Nash
LinkedIn: www.LinkedIn.com/in/stewartnash/

3 Cautions with NPS Benchmarks

2016-04-15T09:12:00.000-04:00

I'm a big fan of Net Promoter and have used NPS surveys for the last eight years, doing surveys for my clients and helping my QuestBack customers implement NPS surveys in their businesses. So this post isn't a "ding" on NPS, nor should it be construed as a reason to not use it. In fact, in my opinion, quite the contrary almost every company benefits from NPS surveying. That said, on to the post....

Benchmarks are a popular in management circles. They're used to defend performance versus competitors, compare performance against industry standards and to justify planned actions to improve the business. This isn't an argument against benchmarks, the have their place. I just think Net Promoter Score (NPS) should not be used to benchmark versus industry or competitors. Lots of folks use NPS benchmarks. I think they shouldn't. Or, at minimum should be really cautious about how they use them.

On its surface, NPS looks like a great candidate for a benchmark. It's based on a standard model. And, successful businesses tend to have high NPS scores, make larger profits and retain customers longer than those that have lower scores. So in theory, it should generally work well as a benchmark. I believe that, in practice, it tends to not work well as a benchmark. Here's why:..

Customer Management Process. In my experience, NPS Scores as given by survey respondents are largely about person-to-person relationships. In my own use of NPS I've found that scores are almost always driven by how well a key relationship is working. Of course, other aspects of a customer's relationship with a company are contributing factors to NPS ratings, but they tend to be secondary. The key relationship tends to over ride the other stuff. This makes using NPS as a benchmark very tricky, because customer relationship management processes may differ substantially between companies. For example, hypothetically two competitors, company A and company B, where "A" has dedicated account and support people, but charges more money. and "B" has neither but charges less. Company A has high NPS ratings and Company B has lower ratings. Can we compare them both to the same NPS benchmark? Probably not. Unless CRM processes, product pricing and products/services are so similar as to be interchangeable, a NPS benchmark isn't insightful.
Observed Promoter behavior and the definition of NPS for your company. This is a HUGE issue for understanding how to use NPS Survey data. Most companies don't understand that unless they correlate their NPS survey scales to observed promoter behaviors. they don't really have an optimal tool for utilizing it. Important promoter behaviors include referral activity, retention and openness to up / cross sell. For our hypothetical companies: "A" has very high retention for customers rating it a "10" on the NPS scale and a very low retention for those "6 and under". "B" has the same retention rate as Company A, but for customers giving them a "7 or higher" and low retention for 3's and under. Clearly the standard NPS survey scale needs adjustment for both of these companies in order for them to properly focus on their promoters, passives and detractors. Again, benchmarking either of these company's NPS scores to a standard would be comparing Apples to Oranges.
Effectiveness of NPS Survey follow-up process. In my observation, effectiveness of Closing-the-Loop actions on NPS survey feedback varies widely among businesses. Some follow up every survey response, some only detractor responses and some no responses at all. Since it is proven that "closing the loop" actions tend to improve NPS scores, benchmarking NPS scores where a "loop closing" process is non-existent or not comparable to whatever the benchmarked loop-closing practices are means scores are comparable. In other words, as a benchmark NPS wouldn't be relevant, at least until loop-closing was done to the same extent and effectiveness as the population in the benchmarked group. Most companies hold closely their feedback follow-up-process data. So, its difficult to discern if your follow-up process is comparable to the benchmark. Another reason not to rely on NPS as a benchmark.

In my opinion, NPS Should be used as a benchmark. But, only internally (i.e. against itself and over time). And even then, it should only be used as a benchmark when the definitions of promoters, passives and detractors are well understood in their NPS context for your customers.

Stewart Nash

www.linkedin.com/in/stewartnash

"ViewPoints" improve Text Analysis Usability

2016-04-01T13:02:00.000-04:00

"It depends on your point of view". In debates or discussion this is a phrase used to suggest different interpretations are available. As human beings, of course, we know that the meaning of spoken words changes with context. With written words though, we often don't have the same ability to infer context. And, as anyone who's analyzed a set of verbatim comments can tell you, how words are interpreted matters a lot to the quality of the analysis.

At Etuma, we've always understood the need for "globalized" views in our analyses. In our product, these globalized "views" are called "Lexicons". Etuma offers a number of Lexicons for Voice of the Customer (VoC) and Voice of the Employee (VoE), in various industries (Retail, e-commerce, Air Travel and others), for instance.

Recently though, Etuma has added a new capability for much more granular views of verbatim comments. We call these "ViewPoints". A ViewPoint is a specific topic subset within a Lexicon. Some examples of different Etuma "ViewPoints" are:

"VoC Retail, Customer Service.
"VoC, Air Travel, Food Service.
"VoC" e-commerce, purchase experience

Viewpoints give Etuma customers the ability to quickly and easily "tune" their analyses so that text is mapped to topics according to the data needs of text analysis users, typically end users of data. Once a ViewPoint is implemented, users simply select it as a background variable for their report and data is automatically re-organized so that non-relevent topics are excluded from the analysis and relevant topics included, regardless of their overall importance to the text stream being evaluated. In other words, without a great deal of effort, ViewPoints let Etuma users quickly see what they want or need to see in their feedback data to better do their jobs. A very useful capability. One I am looking forward to implementing for customers.

Learn more about Etuma's solution set at www.etuma.com

Stewart Nash
linkedin: www.linkedin.com/in/stewartnash

Surveys make Text Analysis Better

2016-03-15T14:02:00.001-04:00

A few months back I wrote a post titled: "Text Analysis makes Surveys Better" (click here to read the post). The genesis for the post was my perception that organizations needed a better way to collect customer feedback than just long and involved surveys. Among others, I made three main points in the post:

Functional customer surveys (those short enough to have high response rates) rely upon open answer comments for key insights into the customer experience.
Comment categorization and analysis therefore is critical to a successful process.
That for low volume processes (under 1000 comments / month) analysis can be a manual process. But, in higher volume surveys automated verbatim analysis adds a lot of value.

As businesses increasingly employ transaction based feedback processes they are coming to rely on customer comments almost entirely for insights. Social media is a key driver for this phenomenon as it promotes a "quick hit" type of process (i.e. select a star and make a comment). Some businesses have implemented single question, transaction based surveys using Net Promoter. Not surprisingly text analysis tools are being used to gain insight on all these comment streams.

As a result, many businesses have moved away from "research" oriented customer surveys, choosing instead to use single question Net Promoter / Customer Satisfaction surveys with open answer comment fields. In effect, these businesses have chosen to rely on verbatim feedback analysis, almost exclusively, for generating insights about their customers.

This kind of feedback management approach has the advantage of being simple to implement and can be effective for insight generation when feedback volumes are small. The NPS metric, or satisfaction metric for that matter, provides base level context for feedback interpretation and analysis. For instance, topics with negative sentiment in comments coming from detractors are generally assumed to have some impact on NPS scores. Where feedback volumes are small, time can be taken to validate the "truth" of that assumption. Without going into lots of depth on this, in my experience the things people talk about in their comments (topics) are often same across NPS categories (i.e. Promoters often experience many of the same issues that detractors experience). So, validating "truth" associated with comments is quite important to building improved processes. NPS or CSAT by themselves are typically not enough to ensure this, as they don't by themselves provide enough context to the feedback.

However, when feedback volumes expand in different ways the need for additional context to customer comments also expands. Some examples:

Differences in regional or country specific comments
Operational differences about how customers are handled (i.e. which call center handled the customer)
Does the same NPS or Satisfaction scale even apply across regions or countries?

Its easy to see that a simple sort of feedback process could be problematic when comment volumes rise and interpretation complexity increases. Some things ameliorate these challenges, at least to a degree. Automated text analysis solutions, for instance. Text analysis tools (www.etuma.com) deal quite effectively with high volumes of comments. And, if there is background data behind the surveys (for region or country for example), these tools can use the background data to provide additional context and better analyses.

But, even in a scenario where automated text analysis is applied to single-question NPS surveys, and background data is available, there is often a need for additional context in order to understand how to best take action on feedback. Some types of additional context include:

Expectations - What is reasonable vs. unreasonable in the customer's mind for any given challenge highlighted in their comments?
Alternatives - Are alternatives available to customers either from the business itself or competitors? Are alternatives reasonable if available?
Costs - Are customers willing to absorb higher costs for improved processes
Business opportunities - Would more customers actually recommend if problems or issues are better dealt with? Would they buy more? Or more often?

These are the types of contextual "truths" that must be learned via an interactive process with customers. Customer surveys (www.questback.com) are by far the easiest and lowest cost way of getting this type of data.

The value add of driving customer insight generation from customer feedback, in my view, is substantial. First, a lot of data becomes available to the insight generation process because of the feedback process. This enables insight generation to be a short easy follow-up survey to the initial feedback survey (which was itself short and easy). With the automation available today via APIs filtered data can emerge from the feedback process and be used to trigger insight generation.

Of course, a process of automated feedback, automated text analysis and automated insight generation requires a single, or group of, integrated system(s). The system(s) would of course require some kind of Analytic "back end" to help make sense of all the data. I am currently working with customers who are putting together this kind of optimized feedback gathering / data analysis / insight generation process. The platforms my customers are using are relatively low cost and are easy to use. So, businesses that want to improve their processes by using more automation for feedback, analysis and insight can do so without breaking the bank, or disrupting their operations.

At the end of the day I find it fascinating how businesses are changing the way they gather and analyze customer feedback and generate insights from it based on technology.

Stewart Nash

LinkedIn: https://www.linkedin.com/in/stewartnash

Feedback Action Management makes QuestBack Essentials - Essential

2015-10-29T16:54:00.000-04:00

Two years ago I wrote post here about the importance of Action Management to customer feedback processes. It was titled: "Turning customer feedback into action is the number one challenge for customer strategists." The article referenced some work done by Walker Information Systems and pointed at an article written by them (click here to read my earlier post and the link to Walker's article).

The point: Customer Feedback is a lot more useful if it is immediately actionable.

One of QuestBack Essentials' main advantages is that it makes customer feedback immediately actionable.
Kudos to QB for thinking that way as far back as 15 years ago. Their Essentials product uses a couple of different process mechanisms to make feedback actionable immediately. One of them is the equivalent to Walker's "Hot Alert" process. QuestBack calls it a "Notification", simply an e-mail that is automatically triggered to a given person based on criteria (a response profile) coming through the customer feedback instrument, which could be an e-mailed survey, a feedback form, a pop up survey or any other QuestBack created feedback instrument. Other process mechanisms include, all responses and manual inspection / selection of response to be acted on. As a result, QB Essentials is very flexible in how it helps organizations create action on received feedback.

In any case, the main issue most organizations have when trying to implement action processes on feedback is determining the combination of "feedback to be actioned" and "how to action it". In other words, hot-alerting feedback for action only works if the "action takers" for that feedback are empowered to act on it in ways that help with the issue. This simply is not the case in most scenarios. So businesses continue to struggle with applying action management on their feedback, even when they have great tools to use like QuestBack.

So what's different now? Well, QuestBack is different. Action Management has been improved in QuestBack Essentials and combined with a Case Management capability to allow customer feedback "issues" to be Highlighted, Status-ed and Actioned - all within the QuestBack Essentials platform. This capability allows new issues to be highlighted, internally discussed and disseminated, decisions to be made and actions determined. All within short periods of time (minutes or hours potentially vs weeks or months today) To my mind, this is really cool stuff and very valuable potentially to call centers, sales forces, hr teams, etc. Really, any group of people in a business who have to react to the concerns of another group of people. And, it has "hot-alert" automated actioning too. This combination allows an organization to standardize action taking on certain kinds of issues, while manually intervening on other issues and inspecting / organizing for yet additional kinds of issues - all at the same time.

Combined with QuestBack's Dashboarding capabilities, this lets companies inexpensively seek feedback, organize and implement follow-up actions and processes, report on feedback and actions, and Manage that feedback effectively based on surveys they do using QuestBack Essentials.

I think anyone looking to implement a closed-loop customer feedback process today would do very well to consider QB Essentials and its action management tools.

Stewart Nash
www.linkedin.com/in/stewartnash/

Continuous vs. Episodic Feedback - Continuous is better

2015-10-02T10:04:00.000-04:00

I've recently received a number of survey requests.

The requests are coming from companies that, apparently, are having business "issues" of one kind or another and are looking for feedback to help them address it. The issues range from "low open rates" on electronic content to subscription cancellations to non visitation to websites.

It's a good thing that these businesses are seeking feedback. And, late is after all, better than never. The feedback these businesses get will help them address the problems they've noted. Though, their remedial actions will come a lot later and as a result be less effective for their businesses than if their feedback programs were continuous in nature. Furthermore, I can't help but think that if these businesses had on-going customer feedback programs, they probably wouldn't be experiencing the issues that created the need for the surveys they're sending out now.

Continuous customer feedback is known to be better than episodic customer feedback for understanding customer experience. This doesn't mean that periodic relationship surveying isn't necessary. For most businesses, both continuous feedback surveys and relationship surveys are extremely important for understanding the overall health of the customer relationship.

Businesses that continuously collect, analyze and act on customer feedback are able to detect issues before they become widespread. This means that actions can be taken to mitigate or eliminate issues before they impact too many customer relationships. This often reduces direct costs and even more often avoids indirect costs (typically discounts given to "make things right" for customers impacted by issues).

Continuous analysis of feedback to detect trend changes is the key to a feedback program. After all, data is just that without analysis. Analyzing for change in NPS or CSAT scores, topic popularity, topic sentiment changes, etc., gives the Analyst the insights to visualize what issues might be cropping up in the business. The tools for generating these analytical insights are now both available and reasonably priced for most businesses.

I work with QuestBack AS for surveys and Etuma Ltd. for text analytics. Businesses implementing both are able to get continuous feedback process monitoring and analytics.

Stewart Nash
LinkedIn: www.linkedin.com/in/stewartnash

Etuma - Best in Breed Sentiment Analysis

2015-09-22T11:57:00.000-04:00

Here's an awesome quote from the Insight Now Blog about Etuma's text analysis solution.

"Arguably the best in breed automated sentiment analysis is provided by Etuma" - Insight Now
Click Here to read the entire blog post from Insight Now

I'm sure its going to generate a lot of discussion on the internet amongst companies using automated text analysis services as well as from vendors in the space.

Sentiment analysis has always been considered the most difficult thing to do when interpreting streams of text based feedback. But, doing it using Etuma, combined with key background variables (like NPS categories or scores) and some "eye ball" time on key sub-sets of comments (Which Etuma also makes easy to do) can give you a very accurate, actionable, picture of what customers or constituencies think about your products, services, systems or actions at different points in time. That an important research house thinks Etuma is the best automated solution means a lot.

Stewart Nash
www.linkedin.com/in/stewartnash

Text Analysis - Understanding Operational Change

2015-09-01T09:50:00.000-04:00

I had a very interesting conversation with a customer recently. The conversation resulted in the customer signing a contract for Etuma's text analysis service (Feedback Categorizer / Insight Portal). I had been in discussions with this particular customer for a number of months with the dialogue going something like this:

- Customer: We really like Etuma's ability to categorize and sentiment rate our transactional NPS Survey feedback. But, we know what we need to do to improve our NPS scores and we're investing heavily to make lots of those changes. So, we can't justify the time and effort to buy and use Etuma right now.

- Me: I understand, resources are tight all around and taking them from things you know you need to do, to do things you may need to do can be a difficult sell. Let's revisit this in a few months when your investment and resource commitments have stabilized a bit. I'll touch bases then.

I've known this particular customer for several years. So, instead of pushing what I knew is good argument for Etuma, I thought it better to just wait until things calmed down for him. So, what changed? Why did this customer reach back out to me and decide to acquire Etuma Text Analysis?

The answer of course is simple. The boss (CFO in this instance) wanted some way of understanding if all the financial and other resources they were investing into "doing the things they need to do to improve" actually were helping them to improve. What happened was this company's NPS scores started rising, which they hoped / expected would happen. But, the question they couldn't answer easily was which of the operational changes they made were driving the change in NPS scores. With Etuma, the changes in feedback, both from a topic perspective and a sentiment perspective, are easily mapped to implementations of operational changes, giving managements a very rapid and correlated understanding of the effects their decisions are having on customers.

Fortunately, implementing Etuma is almost as easy as deciding to buy it. So, getting data on NPS and its changes is a fairly simple matter. Its great to have another Etuma customer. Its even better to see that corporate management is willing to invest in methods for understanding if their actions are producing the results they seek. Better still for this company, the investment needed to aquire Etuma Text Analysis was very modest.

Stewart Nash
LinkedIn: www.linkedin.com/in/stewartnash

Try Etuma for free. Click Here

The Survey is Dead, Long Live the Survey - Part 2

2015-08-29T17:10:00.003-04:00

Four years ago I wrote a post here titled: "The Survey is Dead - Long Live the Survey". At the time over-surveying was a problem being talked about a great deal in the trade magazines and blogs. Response rates were declining across the market research industry. The argument then was that social media data streams would replace a lot of Surveys.

Fast forward to 2015. I think the exact opposite has occurred. Today, more people are being offered more surveys than ever before. And response rates appear to have stabilized or maybe even gone up. In 2011, I said that: "social media may actually increase both the frequency as well as the value received from customer surveys". I believe this statement has been proved even more true than I had imagined it would be. But, its been for different reasons. Or, maybe for reasons related to those I had mentioned. I had thought that social media would force businesses to respond to feedback in more real-time ways. And, today many do so, mainly through on-line chat applications. But, almost all electronic methods of communication with businesses today offer some kind of feedback capability. Virtually all of them employ some kind of survey technology to collect and distribute the feedback.

So, In point of fact surveys today are more ubiquitous than ever before. And the reason is simple, businesses need to know something about the people giving them feedback in order to act on it. Also true is that transactional and even relationship surveys are even more widely used now than then. Again, for the reasons I had described. They simply provide businesses with too much valuable, actionable feedback (at a very low cost) to stop being a core feedback management tool. What has changed is that surveys are being better designed and are a lot more respectful of people's time than in the past. So more people are willing to take them.

Of course survey technology is improving. Today, many web surveys are Mobile Device Enabled (MDE). MDE surveys appear to generate higher response rates. In my opinion, because people can use their smartphones on the subway, train or bus (or anywhere else that's connected to the internet) to take surveys. Also SMS text messaging can be used to deliver a survey to mobile users, meaning people don't even need e-mail accounts to be reachable anymore. Survey links are embedded in social media now all the time, further extending their potential reach. As a result, survey-able populations are larger. And, with larger populations and higher response rates, its no surprise that more surveying than ever is going on.

A plug for QuestBack. All QuestBack Essentials surveys are fully MDE. They can be delivered via URL, Email, QR Code, Pop Up Script, embedded in social media or even sent via SMS text.

Surveys aren't dead at all. They are more alive than ever before, used in more places and for more purposes than ever before and providing more value to businesses than ever before. Long Live the Survey!

Stewart Nash
LinkedIn: www.linkedin.com/in/stewartnash

Surveying in support of unsolicited verbatim feedback

2015-08-25T18:04:00.003-04:00

I've written a number of posts her focusing on ways to employ outbound processes for soliciting customer feedback. But, by definition, outbound feedback collection requires enough customer knowledge to determine which customers to engage, when to engage them and what topics to try and engage them on. Some of that data can be drawn from CRM databases. But, what about when no solid information exists about a customer?

In my most recent post I discussed how text analytics can be employed to categorize verbatim feedback from transactional surveys and how this categorized data might then be used to trigger follow on topic driven surveys. This post is going to elaborate on that topic and extend into other arenas where verbatim customer feedback can be analyzed, categorized and potentially used for input to survey processes.

One important type of unsolicited feedback companies receive is from social media and company websites, where customers visit without being asked to, or are responding to some level of marketing. The feedback businesses get from these sources can be difficult to take action on, unless it is reviewed at the actual comment level. This, of course, takes lots of resource. Text analysis tools are a logical mechanism to employ so as to reduce the manpower needed for follow up. Since topical categorization of social media based feedback is a simple matter today for text analysis systems, using them to create feedback categories is a logical step. However, most verbatim feedback - taken without context of customer data is also hard to act on. So, surveying subsets of customers based on their topic and sentiment profiles also makes logical sense. The same way drill down surveys can help with simple transactional feedback (last months post), they can help with understanding unsolicited feedback.

It seems to me that getting survey questions out to people interacting with social media or survey like data into social data streams would clearly add value to the data. An example of how this might work:
- "Business A" had 10,000 comments come in last month through their web site, where they offered a feedback form with a single NPS question and a verbatim comment box. The 10K comments were run through text analysis. 1000 comments were categorized as referencing "product quality". And, of those, 200 were from "detractors" and 200 from "neutrals".
- In situations like this, the product management (PM) team would want to try and ascertain if product quality was in fact a driver of NPS score. By sending a follow up survey to this specific group of detractors and neutrals regarding products, company A's PM team can generate further and more detailed data about any product quality issues customers are experiencing.

The benefit of a process like the one I'm describing above is that it eliminates the need for a person to go through all the "product quality" related feedback to generate the needed information about product quality issues. People taking the follow up survey would provide quantitative data about specifics of product quality. And, the qualitative data in the text would then make a lot more sense. Reacting to feedback using a process like this would help businesses react to the right issues, as well as not over react to non issues.

With more and more customer feedback being unsolicited in nature, its important for businesses to begin thinking about ways to attach specific quantitative data to the streams of text entering their processes. Adding surveys to text analyses based on results, can help.

Stewart Nash
www.linkedin.com/in/stewartnash

Should verbatim analysis drive customer survey processes?

2015-07-19T17:38:00.000-04:00

Traditionally, verbatim analysis techniques and tools are applied in post survey analyses of customer feedback. But, with the increasing prevalence of very brief transactional surveys and social media channels generally, I'm wondering if the process should be reversed. i.e. Analyze verbatim comments to understand where deeper dive kinds of surveys should be deployed.

I'm seeing an increasing number of companies these days that use a very simple transactional Net Promoter or CSAT survey process. Typically, these firms are asking a single question: "How likely are you to recommend [company] to your family and friends?", accompanied by a comment box. Or, "Rate your satisfaction with [company]", accompanied by a comment box. It seems to me that there are advantages to this kind of process including:

Higher response rates
Really simple and fast implementation of the survey process itself
Low cost

It would also seem that there are some disadvantages to this type of process, including, among others:

Figuring out who should do follow up on received feedback.
Figuring out how to appropriately follow up on received feedback.
The challenge of analyzing feedback from surveys where no questions exist about key aspects of the company's offerings (examples being product / service quality or value vs. competition).

For companies early in their existence, simple easy and low cost are important characteristics for a customer feedback program. But, as they grow, understanding the drivers of loyalty or satisfaction become more important in successfully operating the business. This leads to growing companies using more and more manual resources for feedback analysis, which of course costs money. The way it works: At first, one person is assigned to read, categorize and action issues identified in comments in surveys. When comment volume gets more significant they expand to a team of people. And, so on.

Once multiple people begin analyzing verbatims individually, interpretation issues begin to creep into the analyses. The more people categorizing text the more interpretation issues there will be. Automated text analysis tools are a good next step for customer feedback evaluation when teams of people begin getting involved. They reduce labor costs while improving the quality of the analyses.

Even automated and consistent text analytics isn't sufficient to fully understand the voice of the customer (VOC). Additional quantitative data is also necessary. So, some level of follow-up survey process needs to be implemented. In fact, potentially several separate follow surveys might be used depending on what the verbatim feedback is indicating. For instance, if product or service issues are highlighted by people responding to the survey, a follow up survey asking a few more questions (less than 10 ideally) should be sent in order to better understand what those issues might be.

A number of companies I talk with these days have this scenario where they're receiving lots of multi-channel verbatim feedback, beyond that contained in their transactional surveys. Twitter feeds, customer service chats, feedback forms on the websites, etc., all offer text analysis opportunities and will provide indicators for follow up, deeper dive surveys. Companies should look to Text Analysis tools to standardize their verbatim feedback analyses. But, they also should look for ways to use the verbatim analysis results to drive follow up surveys that lead to a higher level of VOC insight.

Transactional feedback is a key element to any company's customer experience strategy. But, understanding the customer experience is more involved and requires more information about customers than simple transactional surveys can provide. Combining them with text analytics and targeted follow up surveys can provide that richer set of insights.

- Stewart Nash
QuestBack USA
Etuma USA
LinkedIn: www.linkedin.com/in/stewartnash

"Ask and Engage" with Customer Surveys

2015-06-14T11:52:00.001-04:00

Feedback Action Loop

Early on in its history (2001?), QuestBack coined the term "Ask and Act" to describe how its web survey solutions provide companies with an easy mechanism to follow up on customer feedback. But, with only a rudimentary e-mail capability, QuestBack's utility was largely limited to specific feedback projects, typically, research or customer service oriented. That has all recently changed.......

Feedback Based Engagement Loop

Fast forward to today. QuestBack should be renamed to "Ask and Engage". Its html based e-mail tools and media libraries allow marketers to build powerful messaging programs that present brands or introduce products / services, all while collecting data, qualifying or generating leads and prospects, or engaging with customers about various aspects of the company's relationship with them. "Rules" embedded in QuestBack surveys that accompany marketing messages let companies design engagement to maximize the business value from each contact they touch with QuestBack.

So why would a QuestBack based customer engagement program be better than say lead nurturing using e-mail tools? A couple of reasons, rules based follow up means that a "rule" determines what kind of engagement should occur. Should a contact's response profile indicate a certain type of engagement, that can be embedded as a QuestBack follow up "rule" which generates a follow action automatically. Rules can also be constructed, using company data, so that the person who "owns" a particular kind of engagement with a particular class of lead, prospect or customer can be automated into an engagement process.

Since QuestBack operates in social media platforms like Facebook or on company websites, engagement doesn't have to be just outbound e-mail driven. Done well, and using closed-loop follow up, surveys themselves are engagement tools. In fact, they are typically very good engagement tools. Even when going out in pure marketing blasts, 1-2% response rates are achievable. When going to customer bases, qualified leads or other folks with a connection, response rates can be north of 30%, a rate e-mail marketers would kill for.

"Ask and Engage" should be an approach marketers start to adopt more and more.

Mobile Support Increases Survey Response Rate

2015-06-02T13:50:00.004-04:00

There's been lots of discussion about how survey response rates are declining for market research and Voice of the customer surveys. I've always argued that survey design and delivery considerations make a difference in response rates. Though I am not a market research professional by trade, I do a lot of web surveys on my own and for clients. So, I thought I'd share an anecdote about a situation where survey response rate actually increased, and my opinion about why.

If you've read this blog over the last 4-5 years, you'll have noted that I do work with a number of club soccer organizations. In particular, I work with a large regional soccer club, helping them with their annual membership surveys. Notably, this year's membership survey is receiving substantially higher levels of response than identical surveys done in the recent past. The "delta" in response rate appears to be related to changes QuestBack has made in their "Essentials" product that make the club's membership surveys much friendlier for mobile device users like soccer moms, who for sure are heavy users of mobile devices.

By way of background, the soccer club uses a modified Net Promoter survey to determine member loyalty, assess opinion about player development and understand overall experience of members in their programs. They also implement a closed-loop follow up process driven by QuestBack notifications. The membership survey has generally been very effective, helping them to understand their loyalty drivers and areas where improvements are needed across the club.

For survey process, the club does four e-mail "sends" of the survey. An initial invitation followed by two reminders and a "last chance" note to the membership. Past surveys have received response rates of 40% or higher. This year, they have achieved 33% after one invitation and one reminder. If past trends hold true, this year's survey will achieve better than 50% response when complete. Needless to say, if 50%+ response is achieved it will be a milestone for the club and will give them a very useful data set to work with. The loop closing they do should help them greatly with club development next year.

I believe that QuestBack's support for mobile-adaptive surveys is the main reason for the increase in response rates the club is seeing. Earlier this year QuestBack invested heavily in re-developing their survey forms architecture to allow virtually any survey question to be delivered effectively on multiple mobile devices, from i phones to tablets. QuestBack surveys today automatically identify the device being used to take the survey, and then optimize questions for that device. For an organization like a soccer club, where parents may be taking the survey in their car while watching practice, mobile optimization may make the difference between taking the survey or not taking the survey.

Verbatim Comparisons add value to Feedback Analyses

2015-04-28T16:09:00.000-04:00

According to most of the research I've seen about Customer Experience, the single biggest challenge organizations face is taking timely action on their customer feedback. For many businesses today customer feedback collection is an ongoing process where surveys are constantly being offered to customers. Yet, businesses still largely struggle to act quickly on the feedback they get. Often, this is because their analysis and reporting processes are manual, taking days or weeks to produce the analyses needed to understand problems.

Etuma Ltd. has created a new tool for evaluating verbatim feedback with comparisons based on key attributes that allow businesses to visualize differences in topics and sentiments expressed. The new comparison tool enables quick and easy benchmarking of operational dimensions (like geographic areas, stores, products, etc.) against each other or against company-wide averages.

Pinpoint operational issues with Verbatim Comparison in Etuma360

Retailers, as in the above example, can use Etuma360 to compare feedback and sentiment at the store level versus the average of all stores and can thus quickly identify problems needing corrective actions at any of their stores. For instance, in the example above, the "Elm Street" store shows lower customer sentiment scores for Topics "Check Out" and "Queues", than the average for the company. This may indicate store staff is slow staffing registers, registers are malfunctioning or check out staff are not operating registers properly. Or, possibly some other problem. Since short lines and efficient check out processes are key attributes of good retail customer experience, negative scores on these topics indicate action needs to be taken.

Verbatim comparisons are equally valuable in other scenarios. In my own experience I have found that in Net Promoter surveys customers often comment on same topics regardless of their NPS category. So, understanding sentiment differences amongst detractors, passives and promoters is particularly useful for me. With Etuma's new verbatim comparison tool, this is now easy to do. It's my experience that topics with negative sentiment ratings amongst detractors are likely candidates for loyalty drivers that the business needs to improve upon for customer retention.

The thing about Etuma that has always impressed me is how easy it is to get started and benefit from verbatim customer feedback analysis. It also is surprising how affordable their solutions are.

Going "Next Gen" at QuestBack

2015-04-24T10:50:00.000-04:00

Those of you who read this blog will know that I resell QuestBack solutions.

Normally, I don't talk a lot about QuestBack products here, as I want the blog to be focused on customer feedback management topics. Occasionally though a note on QuestBack isn't out of order. And, may even add to the dialogue about customer feedback management and dealing with the challenges thereof. I think today is one of those occasions.

QuestBack has embarked on a new strategy and development push that, in my opinion, will see it become a real player in the North American markets. The company has put a tremendous amount of effort into a modernized UI, device independence, multi-mode delivery, and data access via reporting. QuestBack's analytics were always great and their actioning capabilities top notch as well. So a really good feedback management solution has become exceptional.

QuestBack's new releases, v14 and v15, represent the beginning of QuestBack's "Next Generation" product strategy. v15 is currently available to existing and new customers. And, has been re-branded as QuestBack "Essentials".

QuestBack Essentials is really just a beginning for the company. QuestBack has also brought to market its first Survey & Dashboard Application solution, SalesPulse. QuestBack SalesPulse is a survey based application, built on QuestBack Essentials and our DataVoyager reporting platform. SalesPulse uses pre-built QuestBack survey templates that plug into CRM platforms (Salesforce, Dynamics CRM, etc.) and automatically starts generating operationally useful data about sales processes and people. SalesPulse is mainly targeted at organizations that do sales meetings or have scenarios where meetings occur (physical or on-line) in their sales process. An example of a SalesPulse Dashboard follows:

Over time, QuestBack Essentials is going to integrate with many additional applications, will have more action management capabilities, more analytics / visualization capabilities, more panel support and more social media integration.
All in all a great start for QuestBack's Next Gen initiative.

Learn More About QuestBack Essentials Here

Good Customer Surveys are Money-in-the-Bank

2015-03-25T20:42:00.001-04:00

Being in the customer experience management (CXM) space over the last seven plus years. And, in customer facing roles for a lot longer than that, I've seen first hand how customer feedback can impact businesses in hugely positive ways. At the same time, I see how customer feedback is often mis-used, or worse, goes unused at all. So, I thought I'd post something about the many ways that customer feedback can mean money for businesses. Here's five examples...

The customer relationship survey. I constantly read about how companies are de-emphasizing their customer surveys because of low response rates, non-actionable data or other problems. What I know, from long experience, to be true is that customer relationship surveys are hugely valuable. Consider the math. If you have ten thousand customers, a 10% churn rate, a 25% recovery rate and an average revenue of $1,000 per customer you lose a million dollars of business yearly, and get a quarter of it back after working for it again. If you can cut that by a third, its an over three hundred thousand dollar "gain" to the company, and its less effort / investment put into account recovery afterward. Needless to say, you need less new customers to get back to even and if you get the same number you are up. Customer surveys provide the indicators and insight you need to reduce customer churn before it happens.
The customer relationship survey redux. Companies invest lots of money in developing testimonials. Smart companies just ask for feedback then take the words their customers write, feed them back to the customers along with a request to re-use the feedback in their marketing. Each instance becomes a virtually free testimonial. With today's social media tools, its simple to automate feeds of positive, customer approved, feedback straight to your Facebook page, Website, Twitter feeds, etc...
Sales lead qualification surveys. Companies today invest boatloads of money in in-bound lead generation. They then bombard the "leads" with marketing e-mails (LinkedIn lives off of this). The leads after a while will self select away from the company to avoid bombardment. But, the real problem is that they don't really know who truly is a lead and is worthy of nurturing. A simple survey "leads" what they think of their solutions and likelihood of buying at some future point would produce a much clearer picture of who really is a lead and who isn't. Cost of this? Very low. Business impact, very high as "leads" who self qualify are much better quality (as any semi-seasoned sales guy would tell you) than those who do not. The survey process has the additional benefit identifying leads as qualified before those leads would otherwise do so via a normal bombardment process.
Prospect validation surveys. As a sales manager I have found that sales reps can be opaque at times about their sales funnels. Often they truly do not know why a prospect isn't advancing through the funnel or that a lead hasn't yet defined themselves as an opportunity or that a prospect deep in the funnel in danger somehow. Surveys can provide give them (and you the manager) the insights they need to properly determine positioning in the funnel.
Product / Service value surveys. Product managers are constantly trying to determine what features, capabilities, add-ons, integrations or other "things" they can add to their company's products or services. And, determine which things they do will help the product maximize value to the company. Surveys asking customers for product thoughts (i.e. problems, enhancement ideas, documentation improvements, etc....) are an easy way for this kind of data to be accumulated. Getting product enhancement ideas early and constantly helps product managers keep products current or ahead of with market requirements. Products that stay consistently good relative to competition often have more loyal user bases and higher overall profitability - Money in the bank.

So how to do all this surveying without over surveying customers and reducing responses rates? First off, don't create one big survey and send it to everyone. Segment your customer population, then survey the segments periodically as business needs dictate. For example, survey product users for product management - maybe yearly or twice yearly. Survey decision makers and recommenders for relationship quality 1x or 2x per year. Survey leads for qualification quarterly. Survey prospects for prospect validation - once if in short sales cycle and twice or more if in a longer cycle.

What else to do. Have a process for acting on all the feedback you get. Its important to ask for feedback. Its more important that when feedback comes in someone, somewhere in your company sees it and take an action on it.

Surveying customers in the right ways, at the right times with the right actioning processes in place is Money-in-the-bank.

Learn more about QuestBack and how we can help with your customer surveys.

What's the next consolidation in EFM?

2014-11-14T21:08:00.003-05:00

There's been a large recent influx of new capital going into EFM vendors, either through private equity, or merger and sometimes by both merger and additional equity. So, I thought I'd revisit my thinking on the consolidation occurring in EFM.

All technology markets undergo consolidation over time. Normally, it occurs as the technology itself (whatever it is) grows and vendors adapt to that growth. This has been steadily happening in the EFM space.

A few months ago I wrote about this in a post titled: "More Consolidation in the EFM space." It outlined the merger and acquisition activity going on with EFM. The discussion was about the business consolidations by Verint (Vovici), ConfirmIT (CustomerSat), SurveyMonkey (CustomerSat and ClickTools) and others, including QuestBack. The post is available here:

At the time, I had three thoughts about the merger activity.....

"Thought #1. The EFM space is getting crowded at the top end of the market. Gartner, Forrester, Aberdeen and others have been beating the drum for Enterprise Feedback Management for a long time, at least five years by my count. Since most of the EFM vendors focus their efforts on selling to "Enterprise" class customers, as time has passed more of them have adopted solutions, leaving less growth available to the rest of the players. Hence, acquisitions of high-end products."

Clearly, the EFM space remains quite competitive at the top end of the market. So much so in fact that EFM vendors are competing with market research consultants, who sit at the top echelon of the market and act as strategic vendors to large businesses. ConfirmIT / CustomerSat and even QuestBack / Global Park seem to be pushing into the project space of traditional market research consultants. Market research consulting firms are reacting by acquiring EFM technology vendors. The Empathica / Mindshare and Maritz / Allegiance mergers look like this kind of combination to me.

I'm not sure how this will play out. Consulting firms typically purport to be "tool agnostic". It may be that these particular companies have vested interests in the survival of Mindshare and Allegiance, having brought those products to customers as part of solutions. If that were the case, it argues against the standalone market effectiveness of those products going forward. Alternatively, it could be that the consultants find a strategic advantage to owning their own EFM products. Potentially they've even acquired significant projects or new customers as a result. From the outside there's really no way to tell.

To me though, when I see technology solutions that require large amounts of consulting support to enable success, the benefits of the solution need to be correspondingly large, usually this means enterprise scale. Ultimately, I think that means the enterprise software guys will be sniffing around at EFM companies too.

"Thought #2. Serving the small and mid-tier customer segments normally requires that companies have either scale or distribution in order to effectively market. SurveyMonkey has scale, QuestBack has distribution (I'm a QB reseller), Vovici has partnerships (Oracle in particular) and ConfirmIt now has scale at the high end of the market."

Since publishing my earlier comments there've been changes at these companies. SurveyMonkey, QuestBack and ConfirmIt have all become more potent competitors via organic growth and acquistions. What's really new is that Qualtrics and Satmetrix have joined the ranks of larger players in the market. The common theme among all these firms is that they now all have scale, breadth of market access and technology competency. It's a good bet that all of them will continue to grow. Some may become targets themselves for the software giants out there looking to acquire saas businesses in the EFM / CXM space.

Thought #3. Many of the smaller players in the EFM market have neither scale nor distribution. They have to rely on organic growth while competing with larger, better funded and more effectively structured companies. It is among this group of companies that I expect to see further consolidations. Some companies on the list: Qualtrics, Medallia, Satmetrix, Allegiance, SNAP surveys and KeySurveys. These firms serve Enterprise customers or mid-tier customers using a direct sales or assisted direct sales model. They could all use more scale, more distribution or both.

Not much new here except that the list is smaller. Some companies have moved up and others have been acquired. The rest, in my opinion, will be bought out or will just continue muddling along.

So what's next for EFM?

I see EFM being subsumed into the Customer Experience Management (CXM) space. Businesses today realize that feedback comes to them via multiple channels and in different forms. CXM has been about finding ways to collect and integrate that largely unstructured feedback with standard and more structured feedback processes. The goal being to produce a coherent view of customer perceptions, issues, advocacy and angst as it relates to products and processes. The point is that EFM / CXM's value proposition has moved largely to back-end analyses and visualizations which document insights and facilitate actions that improve customer experience.