How to structure your productized analytics offering
Dec 2, 2019
Did you know that businesses with analytics capabilities are 2x more likely to be in the top quartile of financial performance within their industries than those without?1
I’d wager a guess that you want to see your customers succeed. And since analytics can help them do well, a data offering might make sense.
But where to start? Figuring out how to productize your data is a project unto itself.
Looker has helped many companies get up and running with a monetized data offering through our Powered by Looker embedded analytics solution, so we’ve seen what works — and what doesn’t — a few times. I checked in with some of our experts who have “been there, done that” and asked them to share their experiences helping companies strategize their analytics offerings.
Turns out there’s one strategy that all of them recommend for productizing analytics.
Use a tiered monetization framework for data productization
That recommendation is a tiered monetization framework. It’s a bit like presenting the choice between purchasing (A) a beautiful car, (B) the same beautiful car with an enhanced safety system, or (C) all of that plus a world-class sound system. Would you like the great option, an even better option, or the best experience there is?
Here’s an example of a three-tier framework to kickstart your thinking:
|Granularity of data
||Row and column level
|Ad hoc analysis
||Build reports, schedule, actions, alerts
||Storage only: Box, Dropbox, Drive, AWS S3
||All, including: Slack, Twilio, alerts
||Metrics, filters, reports
|End user type
||View and explore
||Explore with actions
Let’s dig further into the details of the features you can include in your analytics offering.
Which features can I monetize?
So many tasks can be automated using Data Actions. Including them gives your analytics offering instant appeal. Which actions you include in your offering will depend on what your customers need most; so rather than recommend specific actions in a blog post, our experts provided an overview of the types of integrations available.
|Marketing automation and messaging
- Create user segments and cohorts
- Build targeted user lists for campaigns
- Send text messages and alerts
- Automate emails and marketing campaigns
|IT, data storage and administration
- Send and store data sets
- Manage infrastructure and instances
- Turn off instances and servers
|Data science and machine learning
- Send predictive features from Looker
- Run and store model results
- Run and visualize model output and metrics
|Product management and communication
- Create issues and file bugs
- Update open tickets
- Send data to channels and chat rooms
|Application process automation
- Trigger automated processes directly from data
If you want to chew on more creative uses of Data Actions, check out my previous blog post about them. (Spoiler alert: an automated alerting system and carbon offsets are involved.)
Scheduling & alerting
When you embed Looker in an iframe, your scheduling and alerting capabilities come along automatically. Monetize the scheduler by granting your customers access to it based on which tier of service they enroll in with you.
At its basic tier, your productized analytics offering will include reports you make for your customers. Going from no data to custom reports like that is a huge step up, analytically speaking.
One step further: let them build their own reports with Explore access. You can spread this access across different tiers by gradually increasing the Explore capabilities for different price points. For instance, your mid-level tier could let your customers create ad hoc reports, while the highest tier gives them the ability to save their discoveries and refer back to them later.
Data export / downloading
Downloading data can also be offered as a premium feature.
Data can be downloaded in the following formats:
- PDF (for dashboards)
- Excel spreadsheet (XLSX)
- PNG (image of visualization)
- TXT (tab-separated values)
Here’s where your Looker expertise will come in really handy. Say you have customers for your analytics offering, and one of them comes to you asking for the ability to do ad hoc reporting on additional data.
Providing a new Explore for them is the way to do that. And since Explores don’t grow on trees (if only!), you can charge them for building this new custom content.
You can also wield your Looker expertise to develop custom actions, provide access to ready-made integrations from the Data Actions library, create new reports... basically, anything you build or customize on top of what’s included in your tiers can be wrapped into a professional services offering.
Further customize your offering with Blocks and the Looker API
Blocks (pre-built pieces of code you can build off of) can help ease the development of those custom components. Our Powered by Looker experts highly recommend checking out the library to see if anything speaks to your industry or your customers. You might just save yourself some time.
You can leverage blocks for retention analysis, gaming analytics, web analytics, and tons more — there are also blocks to help you customize the embedded analytics environment in which your customers view their data.
So while you can’t directly monetize blocks, you can leverage them to get a head start on customizations and components that you do monetize.
Last, but not least (drumroll, please): the API, a real powerhouse for your productized analytics offering.
You can completely customize your web portal or application using the API. You can also use it to migrate Looks across instances, manage your users and connections, and retrieve metadata about saved content in Looker. Check out examples of API-powered customizations (complete with the code to get you started on similar projects) in this blog post.
Head on over to the documentation page to learn more.
The API is a powerful tool to help make your analytics offering look and feel like it comes from you.
...And now for some real world examples
Even within our three-tier framework, there are as many options for structuring your productized analytics offering as fun cars you could take for a test drive... with or without the enticements of those enhanced safety and audio systems. (Personally, I’d hop in the high-end model and blast my favorite song.)
To help make sense of the process, we asked two companies who productized their data with Powered by Looker to share their strategies, technical tips, and best practices for building and going to market with a product offering to monetize data.
Check out the recordings of the sessions:
Content Strategist, Customer Experience
1 Big Data: The Organizational Challenge