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Navigating the Sea of Customer Data Tools

Hopefully by now you’ve planned out what data is important for you to track. Great work! But customer data all by its lonesome is not that useful. You need to set it up to help you make decisions.

This means piping your raw data to various tools that help you:

  • Communicate with your customers
  • Understand how they navigate through your product
  • Nurture customers who aren’t ready to convert
  • Gather and prioritize product feedback
  • Answer granular questions about your product
  • Attribute new customers to the right channel
  • Optimize your onboarding flow
  • ..and more!

And for every possible “task”, there will be dozens of tools to help. How do you choose which one? And more importantly, how do you narrow in on the right types of tools at the right time?

Yes, that same marketing tech infographic that everyone loves so much. Marketing Technology Landscape of 2015 from Chief Martec

We know it’s a little overwhelming. The key is to think about the job to be done based on your key metrics.

Jobs-to-be-Done

There is a nifty framework out there (mostly used for product strategy) called “Jobs to be Done.” The idea is to frame products or companies as something customers “hire” for a job that they have to complete.

“People don’t want to buy a quarter-inch drill. They want a quarter-inch hole!” Theodore Levitt, HBS Marketing Professor

This same idea can be applied to your search for tools. What job do you need to get done right now? Drive users to your site? Get them to activate quicker? Luckily, AARGH good friends at 500 startups already came up with a clear list of jobs to achieve growth, which they aptly titled Pirate Metrics.

Ahoy, matey!

If you haven’t heard of Pirate Metrics it’s an easy way to break down the different steps of a customer lifecycle that you can optimize.

  • Acquisition: Drive users to your site through various channels and get them to sign up.
  • Activation: Engage users early on by having them participate with your most important feature(s).
  • Retention: Get users to come back, visit and use your product multiple times.
  • Referral: Leverage users who are jazzed about your product to refer others.
  • Revenue: Convert users to pay you money for your services.

Each of these areas correspond to particular types of tools you might use to maximize that step of the funnel.

Acquisition

Activation

Retention

Revenue

Referral

You’ll notice that several types of tools, such as “marketing automation,” can appear in different growth areas. That’s because those tools can support multiple growth functions. Also note that this is not an exhaustive list!

While this framework is really helpful for thinking through the types of “jobs to be done” and tools to use to grow your company, make sure to start small! Realistically, you won’t have the resources to focus on all areas of growth at the same time.

You first need to start with your goals (remember we talked about how to choose a good one), and from there you can figure out how to narrow down on which area to focus.

If you’re trying to figure out market fit, you’re probably focused on retention — what makes people stick around? This will take a combination of analytics and customer feedback tools. If you’re a Series A company with some product-market fit intent on scale, you’re probably focused on acquisition. Your stack might layer on advertising and optimization tools.

If you’ve achieved fast growth, you’re likely working on keeping your users around longer and activating more of them. This is where optimizing behavioral email campaigns and choosing sustainable ticket systems becomes important.

The take away here is that you should focus on using tools to achieve one or two goals instead of introducing all of the tools at once.

Qualitative vs. Quantitative

Another aspect to consider about the tool landscape is if you are looking for qualitative or quantitative information.

Qualitative tools give you unstructured customer feedback — think surveys, livechat, heat mapping, and even session recording tools. These tools are great because they allow you to talk to your users, or get a deeper understanding of how a user is using your product.

We suggest using these tools for product development, when you are exploring new types of features and working to understand how customers are using your existing product in detail. Another good time to use qualitative data is if you don’t have enough users to make quantitative analyses statistically significant.

The tools in this category include:

Quantitative tools, on the other hand, give you hard facts about how folks are using your product. These are great for helping you understand higher level trends in product usage, and they do the heavy lifting when it comes to calculating sums, cohorts, and funnels. If you want to see an overview of customer behavior, then these are the tools to use.

We often see companies using a combination of these tools in product development and growth. If you find a trend like a funnel drop off (no one enters their credit card!) with a quantitative tool, you might want to investigate it with a qualitative one (why are people leaving? what is confusing or not compelling?). If you hear a number of anecdotal stories (this part of your product is useless), you’ll want to see if those opinions hold up with data (what percentage of customers aren’t using it?).

In the following course, “Choosing the Right Stack”, we’ll explore specific jobs and the tools that help, as well as dig into the differences between similar tools.

Finding the Right Tools

Yes, it can often be a struggle to find a tool that fits your business needs. But hopefully this above framework helps give you an idea of how to begin your search.

And, if you want to see how other teams have chosen their tools, you can check out these examples.

The most important thing is to focus on the job you need to do to get your business to the next level! Then look at the tools that can help you do that job. Then get some ice cream or something.

Next article

Why You Should Own Your Data

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