Bouquet: Build Analytics Into Every App
Engineers need dedicated analytics for their own needs
Analytics, an addictive feature in apps
Ever noticed how more and more apps now offer analytics as a feature to their users?
For example: my run tracking app offers a set of graphs about my activities. The utilities company provides online analyses of my electrical and gas consumption over time, with year-over-year comparisons and benchmarks with similar homes. Online banking provides analytics on how my monthly spending is split between categories.
The list goes on. Apps provide analytics because users find them useful and addictive. I always check my stats after a run. I have a feeling that a better understanding of my usage can help me improve what I’m doing: taking more steps per minute running uphill, turning the heater down a notch, buying less stuff on amazon, etc.
I’ve come to expect analytics from the apps that I use. It’s a feature that has become as common as using location services, receiving notifications, viewing HD video.
So how do engineering teams go about providing those analytics features in their app?
Analytics are a commodity, right?
When I ask around about how engineering teams build their analytics, I consistently get the same two answers. The first answer is: “we use Google Analytics / Mixpanel / some other tool for our analytics. That’s how we track user behaviors on our app.”
But then I rephrase my question to get the second answer, the one I’m looking for: not your own internal analytics but the one you provide to your users as a feature. The answer becomes: “Oh yeah well our team built that internally”.
I’ve found that from almost all of the companies I talked to, notably the smaller ones. Yep: the same folks who develop everything else in the customer portal or mobile app, also have to develop this feature called “analytics”.
Really? You’re spending your precious engineering resources rebuilding something as commoditzed as analytics? How can that be? I mean, there are so many analytics tools out there, why are you rebuilding stuff that already exists?
In other words, isn’t this a classical Build vs Buy problem?
Let’s take a look at an example. As a user, I connect every so often to my utilities portal (PG&E) to check out my bill and find out why it’s so d**n high. Analytics have prime real estate on the portal:
In fact, this whole section is outsourced to a specialized company, Opower (that now belongs to Oracle), so PG&E have chosen the “buy” vs the “build”. At what cost? Plenty of sources online confirm that they paid… $90M over 7 years. Now that’s a high stakes project.
The investment is justified by “increasing customer engagement”. I’m not the only one to find these analytics addictive!
Analytics for engineers
How about customizing an out-of-the-box analytics tool? Business intelligence (BI) and analytics tools are designed for internal teams and analysts. They’re loaded with features to slice and dice and present data in every conceivable way in order to meet the needs of business analysts (not end users of your app).
I’ve heard app developers relunctant to pay a license price for analytics that consumes their margin as their number end users and data volumes increase. But BI tools are based on that model.
On the other hand, end users need a cool story around their analytics, something engaging and useful. Something designed by a designer, not an analyst. And that’s why engineers end up building the feature themselves.
To roll it out in their app, engineers need… APIs. They’re happy with web development frameworks, not SQL.
Bouquet, the toolkit for developers to build analytics into their app
So we came up with our new version of Bouquet. It’s a tool for engineers, for software developers to build cool analytics features for their users. With Bouquet, they get the interactivity and the freedom of design and implementation they need to provide the best experience to their own end users, while saving on engineering time and effort.
Download it for free. Connect it to your own database. Create cool metrics — I have solar panels and the solar company’s monitoring app tells me how miles were not driven, how many mature trees were grown, how much crude oil wasn’t used by converting my clean solar production into cool metrics.
Embed those analytics into your product using a simple REST API. No more SQL. Open it up to thousands of users in a secure, reliable way. Use the visualization of your choice. Use the storage of your choice: your database on premise or in the cloud.
And this comes now with cloud-based collaboration that works like magic. Even if your data are on premise, you work with people inside and outside of your organization to create the analytics you need for your app. A business analyst in your Hong Kong office can craft the metrics while your designer in San Francisco creates the mockups and your front-end development team in India can implement it.
Analytics play a key role in making your users happy. In the age of IoT and big data it’s what you will differentiate on.