Dabble DB Blog

Server problem

Avi — Sun, 07 Mar 2010 09:41:46 -0800

One of our servers is currently down. We're working to restore it as soon as possible. We apologize for the disruption.

Update at 1:35 PM EST: the server is now back up and running.

PDF print server maintenance

Avi — Thu, 11 Feb 2010 08:53:15 -0800

Due to scheduled maintenance, our PDF print server will be unavailable on Saturday, February 13, 2010 from approximately 2pm to 3pm EST (7pm to 8pm GMT). That means it will not be possible to create PDFs from Dabble DB during this time. All other service should be unaffected. We apologize for the inconvenience.

Trendly and sheep?

Natasha John — Wed, 09 Dec 2009 07:00:00 -0800

Avi recently spoke at FutureRuby and discussed how Trendly went from being just an idea that would help us understand our traffic here at Dabble DB, to a product that other Google Analytics users would find valuable.

You can check out Avi explaining how we named it, why and how it was developed in this video clip.

Case Study: How the Battery Hen Welfare Trust is Using Dabble DB

Natasha John — Fri, 04 Dec 2009 11:12:40 -0800

As a customer for almost two years, the Battery Hen Welfare Trust (BHWT) is a great example of how people are using Dabble DB in their organizations. Based in the United Kingdom, BHWT has saved over 180,000 caged hens from slaughter to re-home them as family pets since the charity began in 2005. This is only 1% of caged hens, but their initiatives are going strong. With celebrity chef Jamie Oliver on board, it's no surprise that they have found success raising awareness for free-range egg production, as well as educating consumers to be more discerning.

Initially, BHWT realized that their rapid growth necessitated moving away from Excel for re-homing records. The increasing number of users resulted in a lack of consistency in their spreadsheets, and coordinators in particular found Excel too technically-demanding for tracking a lot of data, especially without extensive training. BHWT also wanted the ability to view their data in different ways -- something that Excel does not handle easily or quickly. The spreadsheet system also offered no obvious way for the head office to oversee the booking and re-homing process. They decided to look into an online solution and found Dabble DB. The admin user, Adèle Hall said that “since moving our Excel based files to Dabble a year ago, we now have a system that provides all we need to manage and analyze our hen distribution data."

The main function of BHWT's database is to record and maintain hen bookings, both for the trust's own records, and for the British government. Dabble DB makes it easy to report where the hens have been re-homed and, should there be any outbreaks of poultry diseases in the area, it's a simple task to send a list to the government.

Instead of giving all 46 users access to the entire data set, they have set it up so that each person has access to designated Pages and only sees the data for a specified area. With users dotted all over the UK, BHWT makes good use of Dabble DB's ability to be accessed from anywhere, anytime. They also find the system's usability and flexibility especially useful when they run into problems or when they field requests. Adèle continued saying, "Without the need to involve technical personnel we can quickly provide booking access and statistics for our volunteers and Devon HQ as well as add enhancements practically ‘on the fly’ as our charity evolves.”

Our customers often tell us how handy they find the Pages feature because one can embed data views and forms into other websites. As an example, BHWT has created an Adoption Request Form that the public can use on the trust's site. This saves their coordinators a great deal of time because they no longer have to copy information from an email and into a spreadsheet by hand. (You can check out this form on their website)

Here are some other examples of how the trust uses Dabble DB:

- Creating tax reports
- Monitoring hens' status and wait lists
- Tracking equipment
- Recording volunteer information and availability
- Showing confirmed re-homing dates in each area using a calendar view (this can be viewed here)
- Viewing area statistics of hens, rehoming etc.

Now let's take a look at some of their views:

This form that they created using Pages allows all of the coordinators to add new booking and rehoming information into the database.

After they have submitted the rehomer information, they can oversee all of their bookings in this view,which is linked to a shared page for the co-ordinators. They have conveniently made it so that the most recent bookings are always at the top to allow the coordinator to go back and edit straight away if they spot anything that needs changing after submission.

If you’re like most offices, finding saved documents on your office network can be cumbersome at times. BHWT has created an attachment field that they can attach documents to so that all of their coordinators across the UK can access them at any time.

The Battery Hen Welfare Trust is a busy organization that continues to see massive growth. Since they've started using Dabble DB, they've found it to be an invaluable tool that has grown with them and helped them to get their work done more quickly and easily. Happily, they continue to find new uses for it to help them be even more productive.

If you would like to share how you're using Dabble DB, drop us a line - accounts@dabbledb.com

Trendly & Google Analytics Intelligence: Sometimes 10% > 200%

Andrew Catton — Mon, 16 Nov 2009 20:09:05 -0800

Like many Google Analytics users, we were eagerly waiting to try out Google's new Analytics Intelligence feature. Now that we've had the chance, we wanted to share some thoughts on what it does and doesn't do, and how it compares to our own analytics product, Trendly. It turns out that they're quite different beasts, and we think most analytics users will want to use both.

The short version is this: Analytics Intelligence looks for outliers: individual days, weeks or months that buck the overall trends, whether or not they have much absolute impact on your traffic. Trendly looks for changes in the trends themselves, especially those that, over time, have a large cumulative impact on your overall numbers.

Here's the long version. Web analytics data is noisy: every day, for example, the number of visitors to your website will be slightly different. Usually, any given day's visitors won't deviate very much from the mean, that is, the average number of visitors per day. If you see 950 visitors on Monday, 1150 on Tuesday, and 900 on Wednesday, we could say that you have a mean of 1000 visitors per day, and that the deviations from this mean were 50, 150, and 100 on Monday, Tuesday, and Wednesday respectively. If the deviations are small, they probably don't mean anything - your website didn't suddenly get worse between Tuesday and Wednesday, it's just random chance that they were different. Over time, you can get a sense for what the usual range is, and not worry about fluctuations within it.

What about when the deviation is larger? Say that on Thursday you get 3000 visitors, a deviation of 2000. This is well outside the standard range. Google Analytics Intelligence is designed to notice and alert you to these outliers. That's a useful service; maybe you've been featured on some popular blog, or everyone's tweeting about some new promotion you announced. You'd want to know, and Analytics Intelligence will tell you.

Trendly might notice that outlier too, but it's really designed to look for more subtle changes. Say that the following week, you start getting more days with 1150 and 1050 and not as many with 900 and 950. You might say that the deviations are getting larger, but at some point, it will become clear that what's actually happened is that the mean has shifted: instead of getting 1000 visitors per day on average, now you're getting 1100. That's the kind of event Trendly will notice and alert you about. It may not seem like a big deal on any given day - which is why Analytics Intelligence wouldn't even bother to tell you about it - but over a few weeks, that 10% increase in average traffic will have a much bigger impact than a single day 200% spike to 3000^[1]. It's also much less likely that you would have spotted the change in average traffic yourself, making Trendly's alert (in our opinion) much more valuable.

We'd love to hear other perspectives on this. Please try Trendly and Intelligence and let us know how they compare for you.

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[1] It's also worth asking what happens when you have two changes to different segments: for example, say traffic from a small country such as New Zealand goes from 2 to 6, while traffic from the US goes from 500 to 550. From what we've seen, Analytics Intelligence would be more likely to give you an alert about New Zealand (a 200% increase) than the US (a 10% increase, but reflecting many more new visitors). All of these alerts about smaller segments can be distracting, and it would be surprising if Intelligence didn't soon add an option to filter them out (this is not something the alert sensitivity slider currently seems to take into account).

Trendly, on the other hand, judges an event's importance by its absolute impact on your total traffic. This doesn't mean smaller segments are ignored; they're intelligently clustered together, and changes to them are only reported in aggregate, where they can meaningfully move the needle for your business.