“How does my growth rate compare to other companies?”

That’s a question I get asked often in the course of my job as a growth advisor working at a VC firm and until now lacked specific benchmarks to answer objectively. Many times, I had to resort to anecdotal feedback. As someone who prefers data-driven answers, I aim to do better and am excited to share the results of a recent project.

I had two goals:

• determine bands for year-over-year revenue growth relative to when a company began
• put that growth in perspective by comparing it to the capital used to achieve it

The data set I put together spanned 28 companies all of whom sell to consumers and have taken venture capital investment. Some have gone public or been acquired, while others remain private. Some are part of Madrona Venture Group’s portfolio, while many are not.

I came up with 5 observations from this data set:

#1: Expect to Come out of the Gate Swinging

The data showed that the median year 1 to year 2 revenue growth rate was nearly 700%!

That number is inflated since many 1st year companies do not sell for the full year, but growth was still impressive in the years that followed:

Want to be in the top quartile in year 3? Then you’ll need to grow over 300%. Get to work!

#2: Revenue Growth Rates Can be a Roller Coaster Ride

Revenue growth among consumer companies was volatile from year-to-year. As this chart shows, there was not a clear pattern when plotting one year’s growth against the next:

Rory O’Driscoll from Scale Venture Partners performed similar analysis on SaaS companies and saw a different pattern. Rather than the volatile growth of consumer companies, growth rates among SaaS companies decayed in a fairly predictable way. In his study of ‘best in-class SaaS companies’, the growth rate for any given year was between 80 percent and 85 percent of the growth rate of that same company in the prior year (with an R² of .51 compared to .07 here).

Despite the overall data set showing volatility, there are some companies in our set with more predictable revenue growth. When that occurred, it’s often at companies with an Amazon-like obsession over customers. Cohorts are measured and stronger than competitors. NPS is high and the brand is meaningful and consistent in the eyes of its customers. Even when those elements exist, however, it’s likely growth will be much choppier than many other sectors. Buckle your seatbelts, investors and operators, you could be in for a roller-coaster ride!

#3: Revenue Growth Acceleration is Possible (and Common!)

75% of the companies in our data set had at least one year where the revenue growth rate accelerated from the prior year. These weren’t one-time anomalies either, as over half of the companies in our data set had two years of revenue growth acceleration. Scale’s report on SaaS showed that re-acceleration was far less common. In that report, less than 35% of companies had at least one year where revenue growth accelerated. Two years of re-acceleration was even less common at 10%.

With the shorter sales-cycles, fewer decision-makers, and digital transactions in consumer businesses, it’s much more realistic for growth rates to accelerate relative to other sectors like SaaS. Want that to happen at your startup? That’s what I think about everyday — send me a note and let’s talk!

#4: Year Five is When Challenges Often Arise

Blue Apron, Groupon, and Zynga all went public within 5 years of their formation. Each experienced extremely fast growth in the earlier years that ended up being difficult to sustain by year 5:

The reasons for this vary by company. Slowing growth at Blue Apron is sometimes attributed to rising CAC at the same time cohorts were weakening. Groupon struggles included international weakness and consumer fatigue with its daily deals model, while Zynga faced headwinds in a few areas, including challenges diversifying from a reliance on Facebook.

The fact that each saw growth rate declines shows how difficult it can be to sustain best-in-class growth when selling to consumers.

Again, the best solution I know to avoid this fate is to have an obsession over customers. Redfin (from our portfolio) and Netflix were two who were better able to sustain above the median growth beyond 5 years. What do they have in common (besides the color red)? Industry-leading NPS as spoken about here and here.

#5: Be Aware of Capital Efficiency: How Long Does It Take for Revenue to Surpass Capital

I measured capital efficiency as cumulative revenue by year divided by cumulative outside capital. Individual companies were volatile in this measurement as large capital injections often cause the numbers to fall. The overall pattern, though, was consistent and the median showed cumulative revenue surpassing capital by year 3 (as evidenced by a ratio greater than 1).

Achieving this milestone earlier leads to a clearer path to success and we have a few examples where that was the case. Three notable companies in our data set achieved this milestone sooner: Dollar Shave Club, Stich Fix, and zulily (where I used to work). Each had a different go-to-market approach that contributed to this impressive achievement.

Dollar Shave Club launched with a very successful video that got massive uptake right out of the gate. They paired this with targeted and effective PR and were off to the races. Stitch Fix did little paid marketing and relied on word-of-mouth that was often amplified by bloggers. Zulily likely utilized more paid marketing early on than either but was founded a few years earlier when ad inventory was more affordable. Consumers were excited by the daily deal model and emails could be acquired affordably in several large channels. The company could then effectively convert ‘members’ to long-term valuable customers.

Beyond acquiring customers, all three of the outliers mentioned also exhibited impressive repeat rates relative to their industries. This allowed them to grow revenue through both new and existing customers and do so without the capital that would have been needed if they were more reliant on customer acquisition.

I see a pattern of industry-leading repeat rates often in successful companies and believe it’s one of the key indicators of a company that can grow quickly, maintain that growth, and do so without extreme amounts of capital.

Are you trending down this path?

This story is published in The Startup, Medium’s largest entrepreneurship publication followed by 326,962+ people.

Subscribe to receive our top stories here.

Thoroughbreds and Roller-Coasters: How a VC Looks at Consumer Startup Growth Rates was originally published in The Startup on Medium, where people are continuing the conversation by highlighting and responding to this story.

As a growth advisor to over 70 startups at Madrona Venture Group, I’m involved in discussions like this all the time:

“Facebook and Google are too expensive and it’s doing horrible things to my CAC — what other channels are working for people?”

In many cases, I bring up podcasts as I have seen them be successful with many types of companies.

Podcasts are one of the few channels I’ve seen that can satisfy both brand and performance marketers. Despite all of this, many companies have not yet tested podcasts and Madrona hosted an event last week for startup marketers to try and change that.

Podcasts are a way to reach the ‘unreachables’

Anna Sullivan from Gimlet Media was one of our speakers and referred to podcasts as a way for marketers to reach the ‘unreachables.’ By this she meant the most valuable consumers who have shifted their media habits to ad-free zones like Netflix and Amazon Prime Video. Not only are podcast listeners unreachable while watching shows like ‘Stranger Things’ and ‘Transparent,’ but they are also more likely to use ad blockers when on the web. Podcasts are one place they can be reached and with an ad format that can be extremely effective.

Steve Shanks, our other presenter from Ad Results Media, noted that podcast listeners are ‘leaning in’ and actively listening to the content much more so than with a channel like YouTube so it’s more likely they are paying attention throughout. With endorsed spots that can be over a minute and CPMs in the range of Facebook newsfeed ads, it’s no surprise that the channel can deliver a strong ROI.

Need an authentic connection with host and a clear value proposition to succeed

Podcasts may not work for everyone — to succeed you need a product that hosts can speak authentically about. Steve shared an example of a product targeted at teenage girls that had trouble finding endorsers who could speak authentically to that audience. Much more successful is an example like Indochino from our portfolio. Many of the male hosts of popular podcasts wear suits and other dress apparel so speaking about Indochino seems natural. In one instance with the popular ‘Pod Save America,’ a host even wore Indochino to his own wedding and told his audience about the end-to-end experience. That spot has done well because of that personal story, but also because it is followed by a clear articulation of the brand’s value proposition and competitive differentiation. Steve has seen many campaigns underperform without a crisp and clear value proposition and recommends spending time on this prior to getting started with podcast sponsorships.

It’s important to have infrastructure in place to hit ROI goals

Most of the traffic coming from podcasts will be routed through paid and organic search, so it’s important that you can convert that channel before adding podcasts. You will also want to be able to attribute podcasts and Steve recommends a mix of promotional codes unique to a show as well as a ‘how did you hear about us’ survey as part of registration or check-out. Not having a survey means you are likely under-attributing podcast sales as many people do not end up using promotion codes and even fewer navigate using vanity urls. Having both codes and surveys in places makes it so you can test different offers, frequencies, and shows and optimize towards the highest performers just as you would with Facebook and Google. This approach seems to be working for Steve’s clients as they are expected to increase their spend on podcasts 4x over a 2-year period — can you say that for very many of your channels?

Creating your own podcasts

Though Gimlet is known for creating original podcasts like Serial and Startup, Anna’s group also has worked with brands like Tinder and Blue Apron to create their own branded podcasts. This strategy could work if you have awareness goals or have a desire to change audience perception. A common approach Anna shared is to use data from your product to speak about a topic as Tinder has done with their DTR podcast produced by Gimlet. Brands who have worked with Gimlet so far tend to have larger budgets, but Anna mentioned a few resources like transom and AIR that can help companies with more limited resources explore producing their own podcasts.

No matter the style of podcast you create, it’s also important to make sure you have a thorough distribution plan in place before getting too far as the podcast space can be very crowded. Active podcast listeners dedicate on average 6 hours per week to the medium across 6 shows, so you’ll need to get the word out and provide a compelling reason for them to add your show to their routines.

Looking ahead

Both speakers were optimistic that podcasts would continue to grow and provide opportunities for marketers with many different goals well into the future. More data, new user experiences, and integration into ‘smart speakers’ were just a few of the trends they are keeping their eyes on. If you want to get ahead of these, there is no time like the present to explore how podcasts could be relevant to your business and there are few people with the expertise like our speakers to help you do that.

Why Podcasts Should be Your Next Marketing Channel was originally published in Madrona Review on Medium, where people are continuing the conversation by highlighting and responding to this story.

Over a Weekend and for Under $1000

Most startups fail. Debates about why are nearly as old as Silicon Valley itself. Some argue it was the team and its inability to execute, while others point to the lack of a market for an idea.

Both are critical in achieving ‘product market fit’, but a CB Insights post-mortem study found that ‘no market need’ was the #1 reason for failure.

Entrepreneurs put their heart and soul into these ideas (not to mention their capital), and in many cases the pain of a failed startup could have been avoided with some customer research up front.

In this post, I am going to share three relatively inexpensive tests I’ve used while working at a VC to quickly learn about the market demand for startup ideas.

1. Begin with Face-to-Face Conversations.

Why —

At this point your idea is largely in your head. Prospective customers can’t get inside there, so it’s important to start sharing your idea to see what people think about it.

Understanding their level of enthusiasm is important as is learning about the best way to describe your idea so people can judge whether it’s something they can get behind.

How to do it —

Start by getting to know the person you’re speaking with and the kind of solutions they currently use in the space. It’s important to establish trust so they will be honest in their feedback on your idea.

Then describe how your idea would work, asking them if they understand it and whether it’s something they are interested in.

Pause often to allow them to react and ask probing follow-up questions. Try to understand pros and cons vs. alternatives they are using today and whether they volunteer other people they know who would be interested in using your idea.

Friends and others from your network can be a place to start, but seek out ways to extend your research to people you don’t know.

Even if your network is large, it is not nearly large enough to support a business so strangers will need to understand what you are doing and decide whether it’s something they can support.

The excellent book Sprint by Jake Knapp of GV offers some tips on how to recruit people using Craigslist. I especially like the screening process he describes and have used a similar approach.

When I was researching an idea I had that would ultimately become a sports apparel company still in stealth-mode, we walked around tailgates prior to Seahawks games and asked fans if they had a few minutes to talk about a new business idea we were working on.

We had plenty of takers in only a few hours’ time without offering incentives and gained very valuable feedback.

What you can learn —

You will likely get a mix of reactions from people after describing your product.

Ratios are not the most important factor here — instead you should be looking for evidence that something about your idea creates excitement since people need that to abandon the status quo.

You should also note the types of people that respond in certain ways. In the sports example, we categorized people by the type of apparel they were wearing and this type of segmentation was important in getting some partners interested in working with us.

The most critical piece of feedback you can learn here, though, is a concise and clear way of describing your product that gets some people excited. Do not proceed until you have this as it will be essential for making the most of the next two steps.

Cost =

< $200 for possible incentives; free if you can find people out in the wild

2. Next Put into Context with Quantitative Surveys.

Why —

Here you are trying to understand a broader market response to your idea as well as the segments most excited about it. This builds upon what you’ve learned from step #1 and helps you understand how large the audience for your product could be.

How to do it —

Again I urge you to go beyond your immediate network to get unbiased feedback from strangers. I’ve run many quantitative concept tests using Survey Monkey’s Audience product.

It is easy to use and you can get up to 15 questions answered quickly for $1.50 each (prices go up as you add targeting). Survata and Google Consumer Surveys are a few other options.

No matter the platform, make sure you can download the individual responses as those will be important.

Demographic values are critical for understanding different segments and fortunately you get age, gender, household income, and region for free with Survey Monkey. Be sure to ask for any other variables you think might lead to interested segments.

I’ve asked for presence of children, home zip code, as well as some that are specific to a business we are trying to learn about. I ran a survey to gauge the interest in Wrench, a company we’d later back, and asked for information about the types of cars people drove as well as how many were under warranty.

You can see a preview of that survey here.

The most important section in a quant survey is when you describe the product or service and ask people how interested they are in using it.

Take what you’ve learned in step 1 and use words that you believe will catch people’s attention. I use a 5-point unipolar distribution for answer choices ranging from ‘extremely interested’ to ‘not at all interested’ and being consistent has allowed me to compare results across tests.

It’s also important to understand what customers do today for the problem your product solves. I like to ask about the status quo as well as how satisfied people are with it.

Customers not happy will be far easier to acquire than those who do not have a clearer need. Lastly, I always make at least one question open-ended where I ask if people have any feedback to share.

What you can learn —

Total Addressable Market (TAM) is a key question investors will ask about your idea and quantitative surveys are a good way to find that out.

If more than 40% of total respondents answer in the top two categories, then it looks like you may have a product appealing to a mainstream audience. If you’re below that, then try to find segments of people that cross that threshold.

How big are these segments and can a large business be built for them? Wrench did very well with vehicle owners (a large segment) and certain segments were even higher, which both gave us confidence about their prospects.

I’m also very encouraged when people’s enthusiasm shows in the open-ended response. When we tested Wrench, many people had responses like ‘sounds good — where do I sign up?” Others mentioned that they were excited to tell their friends. Both suggest that people will be willing to pay for a product rather than just express interested in a hypothetical version of it and that word-of-mouth could be a large source of customers.

Cost =

$300 for 200 untargeted responses. Goes up with narrower audience or if looking for more people.

3. Lastly, see if People Act Through Targeted Ads.

Why —

A prospect telling you they are interested in a new product is quite different from buying it. Without a working a product you can’t get that far, but you can get close by serving ads to prospects and seeing if they are willing to take further action like signing up for a waiting list.

How to do it —

It’s important to start market testing ads by considering the type of go-to-market your product is likely to use. If it’s something where people are already searching for solutions, then search is a great place to start and you can test demand on Google AdWords.

If it’s something where a market does not yet exist, then you’ll want to start on a place like Facebook that does better for new categories.

Facebook is the place I most often test new ideas and you can get started rather quickly by building a landing page where prospects can sign up to join a waiting list.

Given their unmatched targeting capabilities, you can also apply your learning from step 2 to get in front of the customer segment most interested in your product.

We did this with the sports idea I mentioned and used Squarespace to build a simple landing page. Next, we brainstormed ad idea concepts and took photos so we could load them into Facebook.

I recommend at least 4 different ad creative concepts since you can rarely predict which will work best and more variety will increase the odds of a successful test.

The final step is the most fun and is where you select your target and see how the market reacts to your idea. It’s helpful to have some experience with Facebook as it’s a powerful platform with a steep learning curve.

Once you start receiving signups, be sure to contact people quickly to start a dialogue with them. They can be a great resource as your idea comes closer to reality and might even be your first set of customers!

What you can learn —

Ideally you will get a sense for customer acquisition costs and can do so by dividing your cost per signup by an assumption of the % that will become customers. You will also learn which type of creative works the best.

Relevancy scores of 7 or higher are ideal and I find it especially encouraging if people tag their friends in the comments or respond verbally with their excitement level as we sometimes see.

Word-of-mouth can be a great tailwind for consumer businesses and this type of activity is a good sign that might take place.

Cost =

$500. This should get you close to 50k impressions depending on the demand for the market to reach your audience. Shoot for a 1% click through rate and a 15% signup rate. Some ad platforms also offer credit to get started that would offset some of this cost.

A 3-step Process to Test your Startup Idea was originally published in Startup Grind on Medium, where people are continuing the conversation by highlighting and responding to this story.

Meal Kits are one of the fastest-growing consumer categories lately and one that I have looked at both as a customer and as part of a venture firm. I’m clearly not the only one paying attention. Tech Crunch reported that sales in the category were already over $1bn and it would not surprise me at all for two or even three billion $ exits to come from the category.

Many have already pored over Blue Apron’s recent S1 filing and surfaced some interesting findings. This is not another of those posts (read this if that’s what you’re looking for). Instead, I am going to discuss how the better experience I had with Sun Basket has led to stronger retention metrics and a brighter future than what I see in Blue Apron.

My experience with Blue Apron

Several years ago, I tried Blue Apron and wrote about my experience. Though I enjoyed the meals, I decided the value proposition was not there for my family to continue being a customer for very long. I came to this conclusion based on the time it still took to get food on the table, as well as the quality of the meals relative to that time. What brought me to this decision was comparing the process using Blue Apron out of the box with selecting the ingredients myself from Whole Foods and re-creating the same meals. I found the quality better the second time and the time saved was small.

Enter Sun Basket

Several years had passed since my Blue Apron experience and getting a high-quality, nutritious meal on the table remains a chore. I had heard good things about Sun Basket from several sources, so decided they were the next service to try. Sun Basket appealed to me both because of their eco-friendlier packaging as well as their solution for specific kinds of diets (paleo, vegetarian, etc.). This set of three meals was on our menu during one of our first weeks using the service:

• Jamaican jerk-spiced pork with kale-blueberry salad (pictured above)
• Seared summer squash with black bean tacos with cabbage slaw
• Falafel pita pockets with lemon-yogurt sauce

Overall we scored Sun Basket’s take on these meals 8 out of 10 with the pork being our favorite. This score was higher than where we ranked the Blue Apron meal kit versions from years ago (7) and lower than the same Blue Apron meals using store-bought ingredients (9). More importantly, the Sun Basket meals took on average 32 minutes to get on the table relative to 40 with Blue Apron.

Putting the Sun Basket Meals Through the Test

A sustainable and strong value prop is a critical ingredient in retaining customers, so I thought it would be a worthwhile exercise to re-create each Sun Basket meal as I did with Blue Apron to see quantitatively the type of value the product delivered relative to making them from scratch.

My experiment to recreate the Sun Basket meals backed up my intuition that Sun Basket was a great value. Here are the results and how they compare to the similar exercise I performed with Blue Apron:

The ‘Benefits of Meal Kit’ column here is important to note: with Sun Basket, I am paying $2.02 more per serving, but saving 17 minutes, and achieving the same quality as if I’d made the meal myself. This is a trade-off I have been willing to make and have now been a Sun Basket customer for several months.

Blue Apron was a different story when I did a similar exercise in 2015. In that case, I was paying $1.46 more per serving, saved 15 minutes, but the quality was lower than if I’d made the meal myself and the overall time spent was 25% longer than Sun Basket. I did not remain a Blue Apron customer for long. However, this was my subjective experience, and I next turned to some benchmark data to find out if other customers had similar retention behavior to me.

Comparing User Retention and Customer Value

Consumer spending data is one of the most useful tools I have as a growth advisor in a VC firm. In most cases, the company with the highest customer values and user retention wins a category and tools like TXN and Second Measure allow you to compare companies on these critical metrics. In this case, TXN data shows Sun Basket’s cohorts spending more than Blue Apron’s during their first 12 months:

Other data I saw showed that user retention and revenue per customer were both higher with Sun Basket and the combination of the two led to 50% higher demand per customer at the one-year mark. Now Blue Apron is much larger and it’s very possible that their customer cohorts looked similar at a relative point in time to where Sun Basket is today, but this data and my own experience lead me to be more optimistic about Sun Basket going forward.

Key Factor = Sun Basket Came Later

One theory I’ve been exploring is whether Sun Basket had any benefits by starting several years after Blue Apron. Meal kits are a relatively new concept, so if consumers are already aware of the category and how it works, then it may lead to more realistic expectations and stronger retention metrics as well as less friction in acquiring customers.

TXN data again proves useful:

it turns out 30% of Sun Basket customers have also shopped at Blue Apron.

It’s not clear how many of those overlapping customers tried Blue Apron first as I did, but I believe Sun Basket benefited from having another company establish the market before them. Sun Basket could then study weaknesses in the incumbents and offer a superior product to a targeted segment of the market (busy, health-conscious eaters like me). The meal kit category seems particularly suited for this fast follower strategy as food is very large overall and it lacks both lock-in and network effects, both of which would make it harder for a later entrant to gain traction.

Looking Ahead

Both Sun Basket and Blue Apron are success stories so far and much can be learned from them. Sun Basket is a business I am very excited about going forward, but that does not mean challenges don’t remain. Based on my experience working at a high-growth consumer company, zulily, I have two pieces of advice for Sun Basket as they grow:

• The first is be very quick to observe and correct any operational scaling issues that could negatively impact the customer experience. In several months as a Sun Basket customer, I’ve had my meals show up a day late once and another time had the wrong meal. Credits were issued in my case and I remain a customer, but others may not be as forgiving. Sun Basket would be wise to monitor the impact these incidents have on customers and closely track NPS.
• Second, it is going to be important to observe the marginal Customer Acquisition Cost (CAC) and marginal Customer Lifetime Value (CLV) of people yet to come. CLV looks very strong so far, but how will that look once the product reaches further into the mainstream? It is common for these incremental customers to be more expensive to acquire than the early adopters. The best antidote to this is to be very diligent about testing into new channels and monitoring cohort values closely and granularly. Blue Apron could offer some inspiration when it comes to new channels as they have found the success with offline channels that I see with many top performers these days.

Applicability to Other Markets

Beyond meal kits, Sun Basket’s success speaks to the possibility of entering recently established markets but doing so with a strong product focused on a large but specific segment. It is interesting and exciting to think of where this model can apply elsewhere. Zulily followed this pattern in the daily deal space starting out with moms and kids and executing at a high level before extending to a broader customer set. Stitch Fix took a similar strategy in subscription fashion following Trunk Club, but for women. More recently, Dia & Co. is applying the Stitch Fix business model to plus-sized apparel.

Do you have any ideas on where else this strategy might take form? Let me know at ryan@madrona.com.

Why Sun Basket is the Investment I’m Hungriest for in the Meal Kit Space was originally published in Madrona Review on Medium, where people are continuing the conversation by highlighting and responding to this story.

Most startups understand the importance of customer data, but few believe they have enough people working in data-related roles. I see this with startups I work with and also in studies that point to a data engineering shortage.

Though I can’t solve this shortage, I did gather some benchmark data on how many resources companies of different sizes have in these areas. I was inspired by a recent Keen.io post on the data teams and data stacks of larger companies and wanted to do a similar study on companies who do not yet have the resources of Facebook, Netflix, Airbnb, and Pinterest.

Study Overview

I organized this study around 3 questions relating to different parts of the data stack as outlined in the data engineering post by Stitch Data:

1. Data Consolidation: How many FTEs do you have that work as data engineers or business intelligence engineers? If some people split this role with other duties, such as software development, then feel free to include decimals for the rough amount of their role spent in this area.
2. Data Warehousing: Do you have a data warehouse for customer-related data? If so, what platform does it use? (examples: Amazon Redshift, Snowflake, Amazon RDS for PostgreSQL, Google BigQuery, etc.)
3. Analytics: How many FTEs do you have working as analysts? Could be people who do product analytics, marketing analytics, operation analytics, etc. Again, if someone also has other duties (like finance or marketing) then you can include decimals.

The people in the first question are the ones that setup data infrastructure. This includes the choices made in the second question, as well as any tools or code that bring data into a data warehouse. It is common for data engineers to also maintain and enforce consistency in data. Maintaining a ‘universal source of truth’ in key business metrics is critical to a company functioning properly and is often the responsibility of data engineers.

The people in the 3rd question are then the ones that utilize a company’s data assets. This could be information workers analyzing the performance of a business or data scientists creating and testing a new recommendation algorithm. People referred to in the 3rd question are dependent on work in the first two to do their job effectively.

Over 50 companies participated in this study. Answers to these questions were expected to vary by company size and sector, so I also collected data on who the company is primarily selling to (consumers or businesses) as well as the amount of funding they have raised. Funding is not a perfect gauge for company maturity as some have bootstrapped themselves to impressive heights, but more funding often allows for more hiring so this was the primary way I segmented companies.

Finding #1: You are Behind the Game If You Don’t Have a Data Warehouse

I have written before about the importance of investing early in data collection, so it was great to see that nearly 90% of companies in our survey have a data warehouse. Even more impressive was that so many of the companies with the lowest amount of funding have gone in this direction:

Setting up this foundation early will allow talented people to find the 2nd and 3rd level insights that can help identify product market fit or new opportunities to scale up in smart ways once that has occurred.

Finding #2: Cloud Data Warehouses Dominate with Redshift the Current Leader

Nearly 60% of those with a data warehouse use Amazon’s Redshift. Also popular were Postgres and MySQL (both often hosted on AWS) and a few companies use Google’s Big Query and Snowflake. Much less common are products like SQL Server and Oracle that would have likely dominated a survey like this a decade ago.

Performance, cost, and functionality of these solutions are all much improved from the options companies faced years ago. This has been a key enabler for companies to be more data-driven and responsive to customers and has allowed earlier-stage companies to more easily compete and gain share.

Finding #3: Even Early Stage Have > 1 Person in Each Category

Respondents with less than $10M in funding had on average 1.20 data engineers and 1.58 data analysts:

Answers with decimals were common with the < $10M funding category. At this level, people wear many hats including in the data world. That is understandable given resource constraints, however, I recommend assessing development team capabilities as a company grows to make sure technical debt is not accumulating before a full-time data engineer or data scientist can be hired. Data silos can be problematic and can result when companies are not being forward-looking enough with their infrastructure.

Finding #4: Resources Don’t Increase Until $20M in Funding

The prior chart showed little growth in both categories up through $20M in funding. Once companies hit that stage, however, both categories begin to increase as both the scale and complexity of businesses go up. Questions at this stage start to arise around centralized vs. embedded analyst resources, which is beyond the scope of this project but something to study as each comes with pros and cons.

Finding #5: Companies Get More Leverage from Data Engineers than Analysts

It was interesting to observe that analytics resources grew more quickly with scale than data engineers did. My theory on this is that the most successful companies combine a solid data infrastructure with a culture of data self-service where people throughout the company are empowered to seek answers to business questions. As a result, the incremental resources in the analytics group were often small fractions of large numbers of people rather than dedicated resources. This arrangement was referenced by a rapidly-growing marketplace company participating in our study:

“Our culture is really centered around data self-service, so a surprising number of people at (our company) actively write SQL and do their own data work.”

I experienced a similar environment at both zulily and Blue Nile. Without bottlenecks around data access, we could move quickly based on what we saw customers doing in many different functional groups. This contributed to a culture of critical thinking that is common with high-performing companies.

Looking Forward

We continue to believe that data will be important if not the most important currency for companies as they grow and that the focus on this area in the early days of a company will only increase as new technologies come online. Already we see services that make it easier to implement these solutions — but that does not negate the need for professional data engineers.

In fact, while improvements in ETL tools and cloud-based data warehouses will allow companies to do more with less, there are also trends that will increase the need for more people working on data. Both consumers and businesses will expect their products to be smarter through artificial intelligence and that will require increasing investments in both categories of people to do so effectively. Additionally, data integration is likely to take on greater importance as companies choose to use best-in-class 3rd party tools that require data flowing through them to reach their potential.

We will continue to monitor how these technologies and the need for resources evolve over time. Please share any observations you are seeing about data with me at: ryan@madrona.com

Data Resource Benchmarks for High-Growth Startups was originally published in Madrona Review on Medium, where people are continuing the conversation by highlighting and responding to this story.

Through my role at Madrona Venture Group advising startups on growth, I meet a lot of marketers using Facebook to acquire and engage with customers. It’s a powerful platform. Unfortunately, many companies are falling short of their goals and are left frustrated with what they see as unrealized potential.

Recently I began a Facebook benchmarking project with the goal of providing marketers in our portfolio with aggregate performance data on different stages of the funnel. This project used 2015 and 2016 data from companies who were targeting consumers. B2B companies were not included in this study, though many have successfully marketed on Facebook and many of the same trends likely apply.

Through this process, I came up with 5 recommendations that companies should consider as they try to get the most out of this large and increasingly competitive channel.

1. Know where you are on the calendar — don’t ignore seasonality

Prior to my role at Madrona, I led a growth team investing millions on Facebook each month. Even with this budget, we were often surprised at how volatile the channel could be. A common explanation for this unpredictability was an increase in demand for ad impressions — supply stays the same, demand goes up, and your scale falls drastically. Our data show that there are three big bumps throughout the year when prices rise — April, September and December. It’s likely the tax advertisers in April, apparel companies in September (back to school and fall fashion shows), and general retail in December that are driving up prices. From our study, January and February featured the lowest prices of the year, so now could be a good time to scale up. Alternatively, April is the highest month in H1 so you may want to hold back spending there in favor of before and afterwards. Just be careful in November and December as prices during those periods that were 2x January.

2. Use in-month pricing cycles to your advantage

Different pricing within a month is another trend that appeared in the data. Prices were 20% higher in the last 10 days of the month compared with the first 10 and they increased throughout the month. Exceptions did apply in a few months with holidays like July and February, but this trend appeared in the majority of months. If you have a set amount you are spending per month, allocate a greater share of spend earlier in the month when prices are lower and your dollars go further. Doing so could lead to a meaningful increase in the efficiency of your ad spend.

3. Make sure visitors have great experience on mobile

Among our companies, 82% of newsfeed impressions occurred on mobile devices. That percentage will only grow. Mobile newsfeed impressions used to come at a large discount relative to their desktop counterparts and they remain cheaper, but the gap is shrinking. Because much of the discount has disappeared and because of how large mobile is, it is crucial for any prospective advertiser to make sure their mobile experience is solid before being aggressive on Facebook. This means limited text, clear calls to action, and extensive testing on different devices and screen sizes. Promoting app downloads and sending visitors to a mobile browser can both be effective depending on the situation, but in each case make sure your customer onboarding gives people a fast and clear understanding of your key value proposition(s) so you’re not wasting money.

4. Understand costs of reaching your audience

While it was once made up of exclusively college students, these days the Facebook audience is much more diverse. Nearly every customer segment is reachable on Facebook which is one reason why so many companies turn to it to reach prospective customers. The breadth of the Facebook audience does not mean, though, that all audiences are reachable for the same price. In our study, impressions served at females were 33% more expensive compared to males. Differences can also be found among different ages, geographies and other demographic qualities. Companies would be wise to understand their audience and what that means from a cost-to-reach standpoint before getting too far along in their Facebook marketing journey. Suggested Bids in Ads Manager has not been reliable when I’ve used it, so the best way I’ve found to learn prices of different audiences is through live testing. Also keep in mind that the more relevant your creative is for the audience you are trying to reach, the more cost effectively you can reach them.

5. Treat alternative placements differently — Instagram does not equal Facebook

Over the last few years Facebook has increased its impressions in places beyond the newsfeed. Instagram and the Audience Network are the two that were used most often by our companies and performance data from those placements made for an interesting comparison to native Facebook ads. Instagram was used most often and, while prices were in the ballpark relative to mobile newsfeed, the clickthrough rate was much lower. This takes us back to social media 101. Think through what consumers are doing on each platform and have that in mind when building creative. It’s different by platform. Don’t waste money running ads that have been optimized for Facebook on Instagram. Alternate placements available through Facebook will increase in the future, so keep this in mind when extending your brand to other platforms.

Facebook can be a great place to reach customers, but it can also be unpredictable and frustrating for many. I hope some of the data that came out of this study can shed some light on what’s happening and leave you with ideas on how to exceed your goals.

5 Things I Learned from Studying Facebook Benchmark Data was originally published in Madrona Review on Medium, where people are continuing the conversation by highlighting and responding to this story.

One year ago I took advantage of a rare opportunity by accepting a ‘growth role’ at a venture firm. My job is to help our portfolio companies grow and this has given me a unique vantage point to witness the difference between successful and unsuccessful companies when it comes to growth marketing.

One thing that surprised me is that there is so much in common even when looking at companies at different stages or with different types of customers. Closely monitoring cohorts, for example, has proven to be just as important at a B2B company like Smartsheet as it has been for a company selling to consumers like Rover. An attribution system that links pre and post-purchase data is crucial to the success at a mid-stage company like Bizible just as much as it is at a later-stage one like Redfin.

Here is more information on those two and other lessons I have learned both from the Madrona companies I partner with as well as my prior experience in growth roles at zulily, Microsoft, and Blue Nile:

1. Invest in Data Collection Early On

A common mistake I see is when a company implements the basic version of Google Analytics and thinks they have their analytics needs met for the foreseeable future. While that approach may help spot some high-level directional trends, it does not allow a company to identify micro trends that can be catalysts for future growth. While at Microsoft in charge of selling subscriptions to Exchange Online in the pre-Office365 days, we invested early in a data warehouse and were able to dive into pageview and purchase behavior to identify the content with the highest conversion rate. Using our data warehouse, we found that a particular case study was 5x as correlated with buying vs. other types and promoted it more heavily as a result. The good news for marketers today is that there are analytics tools available that can be setup much more quickly and affordably than in the past. I am a fan of both Segment and Alooma for event tracking / data pipelines and Redshift as a data platform.

2. Link Pre and Post Customer Data

Many people are surprised to learn that at zulily we had a CAC target in one program that was 50x as high as a target in another. For a time, both were a part of our mix as we could use them to acquire customers for less than they were worth. The reason we could operate this way is that each ‘member’ we acquired was tagged with specific details about where they came from enabling us to monitor their value throughout their lifetime. We did this not only at the program level, but also even more granular like by keyword in paid search. Where I’ve seen companies miss in this area is having a uniform CAC target. In the zulily example, that would have likely resulted in overpaying for the lower-quality traffic and eliminating the higher-quality one. SaaS companies I work with are able to do similar as they can see the traffic sources for buyers and then see which of them led to the stickiest and most satisfied customers over time. Often times programs that are more expensive end up being the stronger performers over time as the long-term customer value is greater than other programs that can deliver cheaper initial customers.

3. Look at Cohorts in Multiple Dimensions

Looking at customers in cohorts is a great way to measure performance and it is great to see an increasing number of companies doing this. Cohorts can be especially valuable in businesses with high repeat or engagement rates as well as subscription companies that need to closely monitor churn. When I do cohort analysis myself, I like to look at two different styles: time-based and behavioral.

A time-based cohort chart like the one below shows the cumulative value of customers based on the time they were acquired. This type of analysis lets you compare groups to see if they are getting more or less valuable at comparable points in their tenures. In this case, you’d notice a few weeks in that the December 2015 was under-performing:

Behavioral cohorts normalize for time and instead look at different characteristics of customers. A few examples of this type are: whether customers came from paid or unpaid sources, which customer segment they belong to, or which device they signed up with. In the chart below, you’ll see values across different programs — let’s hope ‘Program E’ were very inexpensive to acquire!

High-performing companies look at both of these styles often. One of our companies, ReplyYes, noticed in their time-based cohort view that a recent month was trending lower very early on in their tenure. They then looked at a behavioral-based cohort and noticed that a new segment they had been experimenting with was not as valuable as their traditional customers. They quickly made optimizations and saw future cohorts look better as a result.

4. Think of Growth as a Cross-Functional Effort

One of the benefits of tech businesses is the speed of iteration that can be possible. A company can launch a test, see the results, and iterate until they identify a statistically-significant improvement to a key metric. Where this falls down is when all of the steps in this process fall on the shoulders of a single individual (often a head of marketing). A better approach is to look at opportunities like this cross-functionally where developers, UX designers, product managers, and marketers work together toward a shared growth goal. New landing pages and onboarding experiences in particular can lead to step-change style improvement and are most successful when multiple disciplines contribute their complementary strengths.

5. Don’t View Marketing Programs in Silos

With all of the noise in the marketplace, acquiring and retaining a customer can be a very complex system with many unanticipated consequences. Rapidly increasing the quantity of leads can lead to a decrease in the customer experience and effectiveness of retention programs. Increasing the scale of one acquisition program can have significant impacts (both positively and negatively) on other acquisition programs. For this reason, the most effective companies start with what I call a ‘universal source of truth’ metric (like new customers or total revenue) and work backwards to see which programs and tactics are contributing to it.

A common misstep on the acquisition side is to look at pixel-based conversions in individual programs. Individual marketing programs can appear to be hitting ROI targets when doing this even when the overall business struggles because of double or triple-counting the same conversion. A common pitfall I see caused by this approach is over-investment in retargeting programs that look fine in isolation but often times do not when looked at more holistically. To avoid this, start with the total orders or customers and don’t be afraid to A/B test retargeting in particular to see its true impact.

6. Understand ‘Pull’ and ‘Push’ Customer Acquisition Programs

An exercise I like to go through with companies is to classify their acquisition programs based on the customer mindset at the time someone learns about their offering. Doing this tends to group programs into what I call ‘pull’ and ‘push’ marketing. Pull marketing is when customers know about the category and actively seek out solutions on by asking their friends / colleagues or by searching on Google or a vertical-specific directory. Push marketing, by contrast, is when customers are doing other things, but learn of an offering because it is ‘pushed’ to them (like in a newsfeed). Many companies are able to succeed with both types, but typically one will be dominant.

A service or product where most of their marketing is ‘pull’ will often have lower margins. Here it is important to focus on things like page load time and testing different parts of the funnel as small improvements can have a large impact on performance. Alternatively, when ‘push’ is dominant, storytelling becomes more important which increases the need for a strong PR presence as well as high-quality ad copy and landing pages. Even if you are growing nicely due to success in one style, I still find it valuable to keep testing both as a healthy mix tends to lead to the best outcomes over the long run.

7. Explore Offline Channels

Though most people I work with allocate the majority of their media budget to online channels, I see many of the faster-growing ones having some success offline. Succeeding with offline channels will require flexibility when it comes to attribution, but the cost can be lower and it can be a good way to stand out from what can be noisy and competitive online channels. Apptio in our portfolio has succeeded with direct mail and at one time it made up a quarter of their pipeline. On the consumer side, Indochino has been having success with podcasts and at zulily we scaled up quite a bit with TV advertising. If you decide to test offline programs, keep in mind that they can be slower to get started and have higher initial testing budgets compared with online programs so be patient and plan ahead.

8. Be Careful of Unrepresentative Early Customers

As I noted earlier, it is important to invest in analytics early to best understand how customers are reacting to your product or service. An important second piece of this is to make sure that early customers are representative of the types that you will see later on at larger scale. I have seen this lead companies astray when a disproportionate number of early users come from people they already know. An audience of your friends and family can react much differently than a more general audience, so I recommend that companies have a mix of paid and unpaid even in the early days. Doing so and comparing performance across different segments (like in #3) will help you understand how users are reacting in more predictable ways.

9. Don’t Assume Program Performance Will Scale Linearly

Hearing about a new successful acquisition program is one of my favorite parts of my job, but I’m careful to tell marketers who have found something not to be complacent. Problems can arise when people believe performance will continue at the same rate into the future and at greater scale. Increasing competition can cause performance to suffer in addition to declines caused by reaching larger and less-targeted audiences once campaigns get larger. Rather than assuming initially strong performance will continue, I recommend taking a more cautious view that individual programs will get harder and more expensive at greater volume. Doing so will lead to fewer surprises down the line and should also encourage people to stay hungry for new programs.

10. Be Open to Different Levels of Experience in Growth Leader

There is no clear date for when the era of growth marketing began, but many point to 2012 when Sean Ellis coined the term ‘growth hacker.’ Facebook is used as an early example of some of these principles in action and it opened its membership beyond college students only in 2006. Since we are now in 2016, it pains me to see when companies seek out someone with 10+ years’ experience to run their growth team. People who are curious, analytical, fairly technical, and can work cross-functionally tend to be most successful in growth roles and I have found those qualities in people with a wide range of experience levels.

This list is only a start as growth marketing is a rapidly-changing field that is only just beginning. I’m excited to learn more about the successful growth strategies that emerge and whether they fit into this list or are completely different.

10 Lessons from 1-Year in a VC Growth Role was originally published in Madrona Review on Medium, where people are continuing the conversation by highlighting and responding to this story.

First Experience

I had read about Blue Apron and their ‘meal kit’ model before, but did not sign up until my wife and I received the direct mail piece pictured below from them in late March:

This was an impressive marketing piece as it conveyed a high-end brand with quality ingredients while at the same time offering a discount to encourage redemption. I also liked the ‘As seen in’ mention on the back to signal credibility. Erin ended up doing the sign-up so I did not go through that experience, but was told we should expect a fish and two meat dishes to arrive at our door.

Package Arrives

The first thing I noticed when the package arrived was that it was shipped from Richmond, CA to my home in Seattle. This seemed like a long way for products to travel that need to be kept cold (meat, fish, etc.) and also resulted in a lot of extra material to keep items from spoiling. The inside of the box also featured a link to a page on their site to learn how to dispose of the packaging, which suggests Blue Apron receives a lot of customer feedback on this issue.

Inside the box were all of the ingredients I needed to make the three meals in clearly-labeled packages. Blue Apron did a great job communicating a gourmet brand through the recipe cards and letter that came with the food:

Each described some of the more uncommon ingredients (epazote and verjus, in my case) in the dishes that separate the Blue Apron meal experience from what most customers put together on a weeknight. The recipe cards were printed on thick, high-quality paper and featured very detailed close-ups of the ingredients, steps in the process, and the finished dishes that made me hungry just looking at them.

Cooking Experience

The three meals I made were Chile-Blackened Cod, Pan-Seared Chicken Verjus and Navarin-Style Lamb Meatball Stew that you can see below:

We enjoyed each of them with the cod probably being our favorite. Each took me around 40 minutes to make with some of that time hands-on and some of it waiting for things to cook. I was surprised that I still had to do some chopping as that step felt like something Blue Apron could have done for customers to save them time. 40 minutes per meal is approaching my limit for weeknight cooking time, so it seemed unlikely we would be long-term Blue Apron customers even though we enjoyed what we ate.

Replicating Blue Apron Meals

At this point I was curious to learn more about the economics of Blue Apron so decided to replicate the same meals on my own a few weeks later using ingredients purchased locally from Whole Foods. The goals of doing this were to determine:

1. The amount of time saved by using Blue Apron
2. The cost of ingredients relative to Blue Apron’s price
3. How the quality of their ingredients and meals compared to a DIY version

Making a list and getting all of the ingredients back to my home took me 45 minutes. The cost of all of these was $51.26 (vs. a non-promotional price of $60 with Blue Apron). I was unable to buy everything so made a few substitutions like using broth instead of water + demi-glace as Blue Apron had me use and dried instead of fresh epazote.

My wife and I actually enjoyed the second set of meals better and are speculating that the main reason was the presence of higher-quality ingredients in a few places. We felt the fish from Whole Foods was higher quality and we were able to use 100% lamb in the meatballs rather than a lamb and beef blend that Blue Apron used (likely to save costs). We enjoy lots of greens in our meals and in the Whole Foods renditions we were able to amp up the vegetables by using the entire portion purchased (i.e. whole bunch of chard) versus the smaller portion included in the kit.

The end result of this experience left us with this comparison:

1. Blue Apron: $60, 2 hours of time, 7/10 meal quality
2. DIY Version: $51, 2.75 hours of time, 9/10 meal quality

What Can We Learn About Economics of Business?

Armed with the cost data, I now sought to determine a hypothesis on Blue Apron’s profitability.

Based on some knowledge I have of direct mail, I am assuming a combined production, list rental, and postage cost of $0.50 per piece for what I was sent and a 1% redemption rate which together lead to a CPA of $50. With the increasing costs I have seen in some online channels, my guess is places like Facebook are also yielding a similar CPA so $50 seems reasonable for the cost to acquire customers in paid marketing programs.

Even though I spent $51 on ingredients, I would guess that by buying wholesale instead of retail and taking advantage of some economies of scale, that they can get unit costs of $25 per week. My 15 lb. package was shipped ground using OnTrac and their website tells me it costs $15 to ship from Richmond, CA to Seattle. A volume shipper like Blue Apron could likely negotiate lower rates, but with all of the packing material and handling needed, I am going to assume a $15 all-in cost of shipping. This makes total weekly costs for Blue Apron $40.

We received a $20 discount during week 1 and I am assuming many other 1st time customers get that so the revenue is $40 in week 1 and $60 in each subsequent week.

The net of this scenario is then:

($50 Acquisition) + $0 during week 1 + $20 during week 2 + $20 in week 3 + $20 in week 4…

Using these assumptions, customers become profitable during the 4th week of using Blue Apron. For now at least, we did not reach this milestone and are so far unprofitable customers for Blue Apron. What strategy might Blue Apron take to change this? That is the question I turn to next.

Strategic Positioning of Food Tech Market

A key consideration when determining whether customers of services like Blue Apron choose to repeat is how customers perceive the options in the market. Because this space is so crowded, I created this perceptual map as I see things:

I view the market in terms of the quality of the food (x-axis) and the effort it takes to make it happen (y-axis).

Blue Apron and the other ‘meal kit’ options all seem to be in a similar place with food tending to the gourmet side and the effort also being high since you still need to do a fair amount of work before dinner is on the table.

Lower effort options include the pure delivery services that source from restaurants like Eat24 and Grubhub, as well as those that make their own meals like Munchery and Lish. Eat Local is a retailer in my Seattle neighborhood who makes frozen prepared meals that you pick up from their store and then heat up in the oven.

The other two points are Gathered Table and Yummly. Both of these aggregate recipes but still require you in most cases to do the shopping and cooking.

With this market in mind, I believe Blue Apron or any provider in its place would do best by seeking out a less crowded space that also matches the values of their target customers.

Two Alternative Positioning Strategies

The second perceptual map shows two alternative positioning strategies that would make me more likely to keep using Blue Apron or an alternative ‘meal kit’ provider:

Move to the Right: Becoming more ‘gourmet’ would include adjusting their model to include ingredients on par or better than what I bought from Whole Foods. This would also require shifting to a more local supplier model so products are not shipped from several states away but are locally-sourced when available. This is a product I would be willing to pay more for and would keep me a customer longer. Providers moving this way could also partner with local high-end restaurants to source recipes which would reinforce the fact that customers are making meals in their own kitchen on par with what one would receive from a night out at a $$$$ local option.

Move Down: Reducing the labor could be accomplished by having more of the ingredients be meal-ready. Produce could arrive pre-chopped and ingredients that are added at the same time could be combined. This could save 10 minutes per meal which would make a big difference when considering these kind of services for weeknight dinners.

Conclusion

Preparing meals on busy weeknights remains a challenge for my family and many others like us. It is exciting as a consumer to see the different options in this space and hopefully one will emerge that we find enough value in to use regularly. Blue Apron did not reach this point for us with their current offering, but could get closer to that point by adjusting their product in a few different ways like I suggested. I look forward to continuing to follow the food tech market and will be sure to write a future blog post should a competitor win our regular business.

Originally published at www.ryanmetzger.org on April 27, 2015.

Introduction

One of the tasks in my life most in need for a new technology is meal planning. Each week my wife or I figure out how many meals we are going to make, sort through our growing collection of cookbooks or bookmarked recipes for meals that week, and then aggregate the list of ingredients needed before trekking to the local grocery store to shop. This whole process takes at least 2 hours and it often feels like a chore to find inspiring new meals to make. Because of this, I was excited to learn about and try Gathered Table, a new Seattle startup that promises to bring more efficiencies to this very process. The food category is exploding with startups lately, but this format seemed a better fit for us than others because it offered more variety than the meal-kit options (Blue Apron, Plated, Hello Fresh, etc.) or the full-service ones (such as Munchery).

Setup Experience

I originally created a Gathered Table account on my PC. The site explains how the process works and asked me my preferences around the amount of cooking I wanted to do, for which days, and the types of meals I liked to eat. At the end of the registration I learned that Gathered Table is normally $10 per month but was being offered 6 months free. Once my account was created, I was shown a list of recipes from Gathered Table and I picked a few of them to add to my account so they would be included in future meal plans. I also had the opportunity to import my own recipes and did so with one from cookinglight.com. This is a feature I appreciate because it allows us to keep our greatest hits in the rotation. Gathered Table also offers an app and I downloaded it onto my iPhone so I could see how their service performed cross-platform.

Product Experience

My initial menu and related grocery list arrived several days after setting up my account. Many of the ingredients were things we already had, so I modified the ‘pantry’ section of the service to reflect this leaving me with a modest grocery list for the 4 meals that were chosen for me. Three of the four were things I had favorited while the other was presumably based on my preferences. All sounded very good and I was excited to try them. Here are pictures of the four things I ended up making (pepper tofu was the best!):

What I liked

1. Time Saver!: Based on my experience with Gathered Table, I saved between 30–60 minutes of time looking for recipes and gathering ingredients. The grocery shopping experience was also much easier as I used the app instead of a paper list as all of the ingredients were organized by section (produce, dairy, etc.) and I could check things off as I added them to my cart.
2. Takes advantage of seasonal ingredients: The recipes on my menu featured many ingredients like squash and kale that are readily available this time of year in Seattle. I am excited to see how this changes during the seasons as we get into the spring and summer. This is a welcome change from my old approach at meal planning where I often end up paying top dollar for asparagus from South America because it was in a recipe I picked (to say nothing of the carbon footprint!).
3. Good recipes: I really enjoyed the pepper tofu, falafel cakes, and curry that were in my first week’s menu. The omelette was also fine considering how quickly it came together. I especially liked how the sides were similar in style to the main courses which led to well-rounded meals that my family all enjoyed. This was a big improvement over the same old salad that used to be paired with my meals because picking sides was something that often got skipped in my original meal planning process.
4. Cross-platform: There were several instances during the Gathered Table experience when I went back and forth between the desktop and the app. Every time I saw changes reflected instantly in the other platform, which is important when taking a list with you to the store (or even with shared accounts between family members).

What could be improved

1. Incorporate feedback loop into menus and recipes: Several times Gathered Table asked me to provide feedback on their service generally, but I did not see a place to do so on specific recipes or meals. I would like to give each item a star rating a-la Netflix so that future menus can learn from what I like or don’t like. Collecting feedback like this could also benefit new users of the service as their all-important first meals could be tested with past customers.
2. Better Social Integration: The current version of Gathered Table has a find friends section where you can get recipes from people you know. I searched for a few people, but was unable to find anyone I know to test this section out. It would be great if Gathered Table integrated with Facebook to bring my social graph into their service. They could provide the option to connect with Facebook upon signup (which can improve signup rates in some cases) and if customers did this in large numbers it could also lead to some interesting marketing opportunities down the line.
3. Ability to Generate Menu on Demand: When I sat down to setup my Gathered Table account I was expecting to go through the whole process and come out of it with menus and a grocery list. The current version seems to do the meal planning in more of a batch mode so I did not receive my first menu and grocery list until a few days later. Because they have a captive audience upon signup, I would like to see an option to generate a menu on demand that would satisfy customers like me who were excited to get started shortly after signing up.
4. Optimize for email signups: Because of my day job, I spend a fair amount of time optimizing marketing campaigns with landing pages and signup experiences. I like the amount of signup buttons on the Gathered Table homepage, but would like to see them simplify the registration process by creating a basic account first and then asking people to supplement it with their preferences. Email addresses are very valuable and can be used for different types of marketing down the road and asking for as much information as they do likely results in drop-off. I would also remove the coupon code box as I have found that encourages people to stop the registration process to look for promo codes. This is Iikely done to track marketing campaigns, but there are other ways to do this that I have found more effective (you can also see how often people search for coupons by the fact that Google Instant Search shows “gathered table promo code” as the 2nd result).
5. Expand Grocery Shopping Integration: Half of the challenges my family faces with getting dinners on the table is meal planning and the other half is grocery shopping. Gathered Table helps with the first and I have also read about efforts to help with the second. Integrating with local grocery delivery services would be a huge win as a menu could be generated with the food being delivered to my home automatically shortly afterward. Adding this could also help bring more transparency to how much each meal costs as I could start optimizing towards more efficient menus that make better use of shared ingredients. This is not available in Seattle right now, but I’d love to see them partner with someone like Instacart to change that soon!

Bottom Line

I was very happy that I gave Gathered Table a shot and will keep using it to see how it holds up as it gets deeper into its recipe database and other seasons. They are still an early stage startup with lots of potential improvements, including the grocery store integration that will definitely be worth trying once it gets added to the Seattle market.

Originally published at www.ryanmetzger.org on December 10, 2014.

Introduction

Past readers of this blog will recognize my affection for ecommerce companies trying to disrupt and improve the ways retailers have long sold to customers. From buying glasses at Warby Parker, to selling diamonds and jewelry online at Blue Nile, to publishing a new website every day customized to your preferences at zulily, I enjoy learning about and shopping at companies who have this objective in mind. When changing fashion trends and a slimmer physique made it so I needed to purchase a new suit for an event, I was excited to give Indochino a try. I had read about them and was impressed with how one of the founders struggled with his own suit buying experience and used it as inspiration to bring custom menswear to the masses.

My first interaction with the Indochino site was a positive one: the site had a nice layout and was quick to point out “best seller” snipes on several of the items I was considering. With a purchase of this type, I tend to be conservative with my choices and appreciate hearing what others have selected. Indochino’s site also had a detailed section on “why custom” which helped differentiate them from other options and moved me closer to becoming a customer. I ultimately decided on a charcoal suit as it matched the majority of my shirts and ties and seemed to be a good option for the largest number of occasions.

Once I had selected the particular suit, it was time to move on to the customization stage. For this I utilized the services of my wife Erin who had the unenviable task of measuring me in more ways than I had previously thought possible.

Indochino’s website provided very detailed instructions complete with videos that made me confident I was doing the process correctly. They also had clear instructions and images for other custom options like cuff style that helped me understand what I was selecting.

Overall the process of customizing the suit was an enjoyable one as it reinforced their value proposition and made me excited to receive my custom suit in 3–5 weeks.

Product

My suit arrived less than 3 weeks after completing my purchase which exceeded their estimates. It’s always a good idea to underpromise and overdeliver with shipping times so I was pleased it arrived when it did. I liked the presentation of my suit when it arrived — it came via FedEx in a box within a box that made their brand look upscale.

The fabric and quality seemed consistent with my past suits (purchased from places like J. Crew and Brooks Brothers) and it was nice to see the items I had customized like my name on the inside pocket and the interior color of the jacket. I was cutting it close to an event where I needed to wear my suit so I tried it on quickly and decided it fit well enough to use. However after wearing the suit for the evening it seemed like the sleeves and pants were too short. I would ultimately take the suit in to a local tailor to correct this to finally make my suit the right size.

Overall Impression

Though it was disappointing to have to take my suit in for alterations, I remain pleased with my decision to give Indochino a try. The experience of buying a custom suit from home was more enjoyable than heading to a brick and mortar store that would have required either a babysitter or distracting an energetic 2 year old. I also likely saved money in the process and ended up with an item that fits better than one purchased in more traditional ways. That does not mean, however, that the process was perfect as there were several places where I think they could improve. I outline these in the next section along with some tips I have for Indochino based on my own experiences working in ecommerce.

Recommendations

1. Increase number of traveling tailors: the biggest disappointment in my experience was receiving a product that did not fit perfectly and needing to take it in for alterations. To Indochino’s credit they reimbursed me for this expense, but I still had to take time to visit a local tailor and went weeks without my new suit. I strongly encourage them to expand their traveling tailor program that would hopefully help customers like me receive proper measurements from the outset. If the cost of scaling this program independently proves prohibitive, I would encourage them to partner with tailors in major markets to perform this service since the services are complementary and not competitive. They could also gather data on alteration rates and steer customers to the tailors who take the most accurate measurements. My sense is the percentage of customers needing alterations is lower if measured by a traveling tailor and that needing alterations has a negative effect on repeat rates. Testing partnering with local tailors in select markets seems like a quick win and is something I would encourage Indochino to try.
2. Greater investment in several details of customer experience: I noticed two parts of the customer experience where a small investment could pay long-term dividends to Indochino. The first is including a garment bag with each custom suit. The cost is likely low and would likely generate referrals and more word-of-mouth awareness (such as from prospective customers seeing it on a plane or in a hotel room). This would not be easy to test, but they could provide them in a specific geographic market and see if that market has higher referrals or overall sales compared with a control group. The second area where a small investment could pay off is in providing complimentary fabric samples rather than charging for a tailor’s kit. The cost of these is not likely very high, especially considering it’s a large ticket purchase, and they could even include a self-addressed return package to recoup everything but the shipping. Warby Parker offers something similar and it was one of the things that made me confident in my selection. I encourage Indochino to test out free samples to see if it drives up conversion rates and brings down returns as I imagine it could help both metrics in significant ways.
3. Delay mention of referral bonus until product arrives: immediately after hitting “purchase” on Indochino I received notice of their generous referral bonus where I could save $50 if someone I referred became a customer. The referred person also saved $50 on what is a very generous 2-way referral program. While referrals are likely the most effective marketing program for a considered purchase like this and Indochino is wise to encourage them, I do not like to be asked to refer something until I have seen the product in person. The high $ amount also made me feel like I had missed an opportunity to receive a discount of my own and caused me some anxiety about the quality of the purchase I just made. The referral mention included in the package was a much more timely message and I would encourage them to align all other referral messaging with this moment.
4. Tone down remarketing and move marketing budget into upper funnel: ever since visiting and purchasing from Indochino, I have seen many remarketing ads trying to sell me on their products. These have been on the web with what looks like Criteo and also on Facebook with FBX.

This compares to the almost zero advertising that I saw prior to visiting the site. Though the ROI of remarketing might appear to be high, from my experience I question whether funds would be better spent in upper funnel activities. Since I have already made a purchase, is there that much to be gained from marketing to me (even prior to my suit arriving)? Being direct response-oriented on large ticket items is not always easy as my time at Blue Nile taught me, but I feel shifting budgets earlier in the funnel would lead to faster growth in the long run and would be a better use of marketing funds than so much remarketing.

Originally published at www.ryanmetzger.org on March 17, 2014.