Considerations when choosing Product Analytics Tool

In the age of data-based decision making, having no product analytics is akin to sitting in an airport traffic control tower and directing aircrafts while the radar is down. Synonymous with flying blind. Adding a Product Analytics stack to the product-tech-stack involves different dimensions of considerations.

We’re a relatively small startup building a platform that aims to “uber-ify” the restaurant industry. That’s a massive ambition – one that cannot certainly be reached without insights into how our users navigate through the various journeys in it.

We’ve had some instrumentation in place with Google Analytics. We’ve also explored Amplitude as an analytics tool. Choosing the a good product analytics solution comes with several considerations. At the end of it all, we’ve chosen Pendo as our preferred option. (Note: This is not a promotion for Pendo, rather merely how it fit our needs).

Audience for Product Analytics

Who’s the user of the product analytics tool? This determines the level of complexity in various configurations that we can accept in the tool. If the users are limited to data analysts, there’s a different set of tools that one could choose. On the other hand, if folks that are not that familiar with different aspects of data analysis and product usage, then simplicity is preferred. In our case, we’d like the larger organisation to be a part of this journey – hence simplicity is key. For the extreme data-analyst use-cases we already had the required instrumentation.

B2B vs. B2C

In an early-stage startup, the number of users can vary significantly. In our case, we have several orders of magnitude more guests (B2C) than B2B users (customers). We did not feel the need to invest directly in tracking the usage of guests on our guest-facing app in the B2C scenario. Instead, we relied on some rudimentary proxy metrics for tracking. Consequently, we chose to stick to the B2B scenario, as tracking behavior in this context was paramount for us.

User Identification:

This is trying to distinguish between logged in users vs. unknown visitor. How will we identify the the unique-user and capture the journey? In our case, we wanted to track logged in users from restaurants and bars. In our platform, we do not yet track guests uniquely in detail and is not the intent in the near medium term.

Event Tracking Flexibility

Who can add new events for tracking? In some tools, developers need to add specific event tracking every time someone wants to track an event. In others, the tool logs all event tracking by default, and even a non-technical person can “tag” these events. With a small team of developers, we opted for the second route, giving us the flexibility to not tie down developer time with event tracking. Also we had the neat little benefit of retrospective event tracking – i.e. If a button existed for a long time, and one fine day I want to start tracking it, I have the ability to get the historical data out of it.

Diverse Analysis Options

This can vary based on the need of the teams. Cohort analysis, audience segmentation, behavioural usage, stickiness metrics, other pre-defined product metrics – there’s a whole range available.

Additional Functionality

What other functionality could you benefit from? In our case, we have a 3rd party tool for in-app guidance. This is a standalone solution that also does NPS surveys. We are lacking at this time a streamlined tool to gather customer feedback directly into our product-oriented systems. With the tool we opted, we could combined product analytics, NPS and in-app guidance – so that served our purpose quite well.

Pricing Product Analytics tools

Obviously important at every stage of the growth journey – just how much is one willing to put in against the value you get out of it. We’ve started with a paid version of the tool. However, there are ‘free tiers’ worth exploring based on certain parameters.

Integration Capabilities

There are range of third party tools that can integrate with the analytics tool and give added value. These are some additional goodies to explore – how crucial can this be? With the additional functionality around NPS and in-app guidance, we are able to analyse product analytics and target in-app guidance based on HubSpot data that is brought into our product analytics tool.

Next step

Time to play around and deliver impact with analytics