How to transform data points into airtight narratives

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We’ve all been in a meeting where there’s a senior engineer or executive poking holes in the data and decision-making you’re presenting. If you’re not prepared, it can be uncomfortable.  It’s easy to have responses for simple things such as, “Is this bug important?” or “What’s our churn for this month?” – you can rattle off numbers. But responding is harder for more complicated questions that involve “why” or “how,” such as, “How should we increase engagement for our product?” or “How do we address our high churn rate?”

High performers at Facebook and Tesla always had well-thought out answers to these deeper level questions. Instead of a shallow narrative that ended at a data point, they all had a level of thoughtfulness that led to a rich, bulletproof narrative. As a result, they garnered respect from their peers because of the confidence they built around going in this direction vs. that direction.

Here’s how I’ve reverse-engineered their process to gain the same level of influence and respect from my team and executives.

Shallow narratives vs. Rich narratives

Data points alone create shallow narratives. Here’s how to transform these data points into a rich narrative with actionable insight for your team.

1. How to present a data point

A shallow narrative is numbers-based. A rich narrative looks for drivers of that number.

Let’s say you’re a product manager at Toast, the restaurant management system. You’re collecting metrics about the health of the customer funnel, in order to create a roadmap for the next year.

A shallow narrative points to metrics: “Our customer churn is 1%,” but then stops there. Here, there’s no context about the numbers and how to determine whether 1% churn is something to be concerned about.

A deep narrative says, “The churn is 1%, but what are the drivers of this churn? All the restaurants who are no longer using Toast are restaurants who are going out of business. We’ve never lost a customer to another cloud-based restaurant management system.” With this deeper understanding, you may decide this number is good enough, and not include any roadmap items related to churn for the next year.

A deep thinker digs beyond the surface, not stopping until they know where the churn is coming from, and all the levers that drive that churn number.

2. How to explain a situation

A shallow narrative jumps to an answer. A rich narrative lays out various scenarios.

Let’s say you’re a product manager at Spotify and trying to increase engagement. What does engagement mean, and why is it important? 

A shallow narrative jumps straight to a single way of quantifying engagement, “Let’s define engagement as weekly listening time. If listeners are listening to Spotify, it means they’re getting value out of it.”

A rich narrative talks through the various scenarios of what engagement could mean. “Engagement could mean many things for Spotify. It could mean listening time, or maybe we’ve changed our organizational strategy to being more social and want to measure the number times music is shared, or the number of friend connections users have.”

In the first universe, Spotify is just trying to do better at what it’s always done before. In the second universe, Spotify might be considering a more competitive strategy, e.g. if say, TikTok or other social platforms are launching their own music streaming apps.

Laying out various scenarios rather than jumping to one scenario forces you to an expansive mode of investigation. This expansive mode is helpful for catching emerging trends, and preventing yourself from jumping to the first conclusion that comes to your mind.

3. How to predict how a decision will turn out

A shallow narrative considers implications for only one player. A rich narrative considers implications for every player involved.

Let’s say you’re a PM at Fiverr, a gigs marketplace that originally allowed sellers to post $5 gigs. A shallow thinker might say, “The $5 gigs are a gimmick that will drive customers to come to our platform.”

A deep thinker will think about the different players in the ecosystem – in this case: buyers and gig sellers. “For buyers, they will be quick to purchase gigs and do so repeatedly, because the $5 eliminates negotiation and hesitation. For sellers, it forces them to be creative and efficient enough to make a profit on $5.”

When thinking about the implications of a decision, push yourself to go from considering just one type of user, to various other users. Considering various users in the ecosystem is helpful especially because users don’t make decisions in isolation – their decisions will have follow-on effects to other user behavior, which feeds back into your overall understanding of your product.

You can create rich narratives not only with data, but also with qualitative statements

Let’s say someone makes the statement: Facebook is a company that executes really well.

• A simple narrative stops there, “Yep, Facebook is really good at execution.” 

• A rich narrative asks, “Well, what are all the conditions that made it possible for Facebook to be very good at execution?”

In the second universe, they might realize that there are external and internal drivers that lead to Facebook’s strong execution. Externally, Facebook is in an industry that changes really fast where executing and learning from changing consumer preferences is important, because consumer preferences are changing all the time – so Facebook needed to evolve into a well-oiled machine in order to succeed as a social network. Internally, Facebook created a performance review system that rewards execution, where engineers and product managers are measured by how they’re driving the team’s goal metrics.

Now that you understand these drivers, you can have a richer discussion about Facebook’s execution strategy, its competitors like TikTok or BeReal, and perhaps whether their execution strategy is long-term sustainable. 

With this new approach, you can generate insights from any simple datapoint or casual statement, creating a rich narrative to influence your team. Let us know and reply if you’ve found this helpful and applied it in your own work. We love hearing from our subscribers.

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Have an interview coming up and want coaching?

Adrienne offers interview coaching to candidates applying to product manager roles. She’s a former PM at Google and Tesla and has given over 100+ mocks, helping her candidates receive offers from top tech companies including Stripe and Lyft.

Practice 1-on-1 with her and have her guide you on how to ace product management interview questions at top tech companies.

Book an interview coaching session here.