Defining Your Analytics Strategy

Setting up Metrics - the right way

The Snippet is a Weekly Newsletter on Product Management for aspiring product leaders.

Imagine you are building a rocket ship. You’ll need all the engineering, design, and fuel to launch it into orbit. But one of the most important things you’ll need is onboard data and diagnostics from the rocketship. The onboard diagnostics are instrumental in steering the ship as it attempts to get into orbit.

It's the same with building & launching products. You’ll need all the Engineering, Design, Sales & Marketing investments to build and launch a product, but to really get your product to grow and sell — you will need a constant stream of diagnostics from your product. Without this data, you’re flying blind, isn't it?

Of course, you know this. But here’s an observation.

While many Product Managers understand the need to have inbuilt Product diagnostics & metrics and hence bake them into their products at build time — Sales and Marketing metrics are often an afterthought for product people until very close to the launch.

I’ve seen this happen over and over again, especially in organizations where Marketing & Product teams operate in silos until ‘its time’ for launch planning.

The way it unfolds is  that  the PM prioritizes building the Product, bakes in Product metrics, and considers their job done. Then Sales & Marketing comes along with a Sales & Marketing plan and requests that additional analytics be added to the product. The end result? Lots of rework & increased build costs, and a mish-mash of analytics tools, somehow cobbled together.

But there is a better way. And that is to define an “Analytics Strategy ” for your Product.

Analytics Strategy for a Product

The analytics strategy for any product defines a wholistic set of metrics that must be captured for it to be successful. The PM must take the lead and work across the Product, Marketing & Sales functions to layout the top metrics that will be needed to steer the product to success. Here’s how an Analytics Strategy helps

  • It forces early engagement — the functional teams, given their strategies start thinking about metrics much earlier rather than later in the game

  • It helps you choose the right analytics tools —  avoiding Frankenstein-ing and unnecessary proliferation of analytics solutions and standardizing on a few quality tools.

  • Significantly Reduces development rework— you have fewer analytics engines to integrate and wire up —  while still enabling the metrics each functional area cares about.

Measuring what matters

Figuring out what to measure and what metrics each functional area needs to get the rocketship into orbit in and of itself requires some serious strategic thinking. It is not easy.

To do this you’ll have to take a good look at your product lifecycle, the business model, the reason why your product exists, the financial objectives, and then define and instrument a set of metrics that help you drive towards those objectives. I’ve written at length about this topic here.

Once you’ve brainstormed and thought through the metrics that you’ll need to measure & drive growth — then comes the real but often underappreciated challenge of choosing the right tools & instrumenting the metrics across the entire customer journey. Most importantly across the Market Awareness, Customer Acquisition, Onboarding & Retention phases.

Zoom Out & Vizualize the Customer Journey

Let's say your team is working on a product — say, its a B2B Enterprise Software.

Take some time to zoom out and get a bird’s eye view of the customer acquisition journey. Here’s what a typical customer journey might look like.

  1. Thanks perhaps to your digital marketing efforts, a visitor lands onto your product’s landing page. They read the information on your landing page and learn about your product. They get interested and respond to your “Call to Action” sign up form and leave you with their email address.

  2. If your customer acquisition is largely online and self-service, this visitor may instantly become a user of your product by signing up for a free trial. On the other hand, if your product involves offline sales channels, somebody might contact them to close the deal and sign them up. 

  3. After a few days/weeks of free usage/marketing campaigns/ sales follow-ups, this visitor might convert to become a paying customer.

  4. Once you have them as a user and/or a paying customer, you’ll want to make sure they are having a great experience using your product. You’ll also want to know if they are having a less than stellar experience — and are likely to leave you soon for a competitor.

Next, map this journey & define an end to end analytics strategy for your product.

To do this,

  1. Ensure that you and your team have identified and defined key metrics across each of the 4 steps of a typical customer’s journey above. For this product specifically, you must have defined — (Step 1) Landing Page metrics, (Step 2) Lead Funnel Metrics, (Step 3) Conversion Metrics & (Step 4)Usage & Retention Metrics

  2. Metrics in each stage must feed into and influence your decisions for the subsequent steps

  3. Identify the tools that will make it possible to instrument these metrics across each of the steps.

  4. That your product development timeline & costs have baked in the effort it would take to instrument these metrics.

What gets measured gets better

Without a well thought out analytics plan, your product will be akin to a rudderless ship and will not reach its full potential.

On the other hand, defining a robust set of metrics across all the critical areas of your Product’s Go-to-Market and Customer Adoption plans will give your team the necessary levers to course-correct your own rocketship and position it into orbit successfully.

In the next post, we’ll dive deeper and look at each stage of a typical customer acquisition journey and talk about the most important metrics that must be measured at each stage. We will also discuss the tools available to help instrument these metrics because that’s where a lot of implementation issues can show up if it’s not planned properly.

Thanks for reading! If you have questions or insights or feedback - Find me on Twitter!

The Snippet is a Weekly Newsletter on Product Management for aspiring product leaders.

Image Credits: Kai Dahms