You're at Level 3:
Data-Driven Optimization

You have business-wide KPIs, and you measure the effect of product, marketing, and customer success changes on those metrics. You segment your users and are beginning to build personalized experiences.

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Performance levels
Access to insights
Depth of insights
Completeness of insights
Coffee Consumed
avatar
Access to insights
Depth of insights
Completeness of insights
Coffee Consumed

Your Mission at Level 3:

Objective 1

Drive conversion, engagement, and retention metrics. Focus on improvements targeted at specific cohorts of users. Build key customer cohorts by incorporating both behavioral, acquisition, and demographic/firmographic attributes.

Objective 2

Establish a key owner of your experimentation efforts (this is traditionally done in growth, product, or customer retention teams). Measure the impact of each experiment and combine iteration and innovation to get a competitive edge.

Objective 3

Leverage a data warehouse and BI tool to further exposure to data and dive deeper into your analysis. Set up clear best practices around self-serve analysis and when to involve the data team.

How to Power Up to Level 4:

You’re not in Kansas anymore—you need more than just one or two people managing your data. Make sure you have a data analytics team that includes analytics experts and data engineers to help support company-wide reporting.

Now that you’re getting some robust insights, it’s time to start prioritizing your data roadmap. This probably means it’s time to unsilo your data. Plan out how you want to use data 3 months, 6 months, and 1 year from now and how to get there. Does that means more experimentation? Collaborating with other teams? Put together and plan and begin to work it. Remember data will always involve some reactive component so make sure you allocate time for long-term, highly leveraged projects and support your team’s immediate needs.

As you build out your personalization efforts, make it a goal to get a 360-degree view of your customers. This means integrating even more data sources to enable a more in-depth analysis of both customer behavior and demographics. Your 360 view can serve as the basis for attribution models, machine learning, predictive cohort generation, and more.

Heap Data Maturity Curve Quiz Level 3

Get a complete picture of the Customer Data Maturity Curve.

Challenge your Friends

Share the customer data maturity curve with your team.