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.
I’ve developed a five-part process for an end-to-end project like this:
- Market research
- Health of the market
- Technical product requirements
- Customer research
- Finding pain points
- Crafting jobs-to-be-done
- Creating user personas
- Product identity
- Messaging and value propositions
- Brand and tone of voice
- North star metric and designing product onboarding around that to drive early growth
- Running a beta and launching the first release
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:
- Different segments of the market
- Market growth for the past three years
- Projected growth for the next three years
- Innovations over the years and challenges to come as stated by existing companies, industry analysts, and industry reports
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:
- Competitive analysis of all submarkets of the wider analytics market (web, product, mobile app, session playback etc.) taking in the top 10 players of each
- SWOT analysis of markets and companies
- Messaging overview of the top 5 companies in each submarket
- Portfolio comparisons of companies in each submarket
- Core technical product requirements for each submarket (i.e. what do we need for an MVP)
Customer research and jobs to be done
Next I carried out customer research:
- Surveys and interviews with clients who’d had issues with product analytics
- I joined various product-focused Slack communities and:
- Found people willing to talk about their problems with current analytics tools
- Asked questions about current analytics and common problems they solved
- Monitored chats for people asking questions about analytics, those with issues with their current analytics, those who seemed to have a problem not solved by existing software, and people who wanted to move away from their existing solutions
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 find the jobs to be done framework helpful for creating 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, and a suggestion to perhaps look at another market, the Directors decided to go ahead with the project.
Leaning on the user personas, I created:
- A positioning document outlining where in the market the product should stand, what it delivered, and how it helped customers complete their jobs
- Messaging to comunicate the positioning in the form of a value proposition, style guide, and content
- A sales site communicating the positioning and messaging
- A social media presence
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:
- Sought out constant feedback on product usage and messaging with weekly questions like “What has the product helped you achieve this week?”
- Relayed customer feedback to the product and engineering teams so they could iterate on the product
- Constantly tweaked the message based on user feedback and product changes
After a few months of beta the product idea had been somewhat invalidated. The product and engineering teams had struggled with the stability of the product after some scary scaling issues during the beta. And, as research had found, this was a tough market to compete in with some powerful tools offering mature fetures.
As of early 2018 I was no longer working on this product. But the process of taking an idea, building it into an MVP, and launching taught me a great deal about product development, market requirements, customer research, and creating marketing campaigns.