Building an analytics SaaS product from scratch

The software studio I was working for was trying to move from client revenue to product revenue. The Directors wanted to build a product analytics tool. Problems faced by clients had led them to believe there was a gap in the market.

I was responsible for defining the requirements for an analytics product as set by the market, devising the go-to-market strategy, and driving initial growth.

Process

I’ve developed a five-part process for an end-to-end project like this:

Market research

Analytics is a mature market so there was plenty to chew on.

Health of the market

I first looked at the overall state of the market:

2018's Magic Quadrant for Analytics and BI platforms from Gartner's yearly industry report. Just one of the many industry reports I looked at during market research.

 

Competitor research and product requirements

A deep dive on current players was up next:

Customer research and jobs to be done

Next I carried out customer research:

Research unearthed some common themes which I used to define a set of jobs that a new product analytics tool would meet. These jobs informed the first user personas and went on to guide the beta version of the product and marketing activity.

I always use the jobs to be done framework to create personas because it helps remove assumptions from marketing and keeps the message centered on overcoming problems.

I presented the market and customer research to product and engineering. Despite the ‘product’ segment of anlaytics being one of the most competitive with extensive product capabilities needed in order to compete, the Directors decided to go ahead with the project.

Product identity

Leaning on the user personas, I created:

North-star metric and onboarding

Part of product marketing’s remit was to build the onboarding for the product. Knowing the core jobs to be done and the product’s capabilities I defined a north-star metric to guide growth and onboarding. The sole purpose of onboarding was to get people to achieve the north-star metric and thus realise the value offered by the product as fast as possible.

I opted to use a low-touch messaging approach using Intercom and behavioural triggers to deliver action-based onboarding. For example, helping people install the tracking code and automatically letting them know when data is showing so they can start analysing data. In this case, creating a funnel.

Launch and beta

With an MVP built we wanted to test and build on the idea fast. We launched at a product conference offering lifetime discounts for the lowest pricing tier to all attendees interested. Hundreds of people took up the the offer and we were able to test the messaging and product at some scale.

At this stage the product was still in beta. Over the coming months I oversaw the beta where I:

After a few months of beta the product idea had been validated. Product-market-fit was still elusive but there was enough to move forward. The product and engineering teams were happy with the stability of the product after some scary scaling issues during the beta. The product was ready for its first release and relaunch.

As of early 2018 I was no longer working on this product.


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