Here’s what startups should keep in mind while tracking metrics: Gaurav Ranjan of Prime Venture Partners

In this episode of Prime Venture Partners Podcast, Gaurav Ranjan, VP of Investments at Prime Venture Partners, talks about the importance of tracking metrics for early-stage startups and what they must consider for transitioning to data-based decision making.
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Gaurav Ranjan, VP of Investments at Prime Venture Partners, believes that there are three broad objectives of tracking metrics for early-stage startups: quantitative assessment of business health, sense of control and transparency across the organisation, and data-driven decisions.   

The first dilemma for many early-stage startups when riding on gut feeling and emotions is understanding the transition from gut-based to data-based decision making. Metrics-based decisions are made after tracking metrics (collecting data).

Gaurav says this needs to be done from day zero onwards as this data will provide the “necessary insights during the early days when startups are trying to figure out product-market fit”. Once they can see repeatable growth in the next 3, 6, 12 months, startups can move towards metrics-driven decisions.

“Again, there is no clear transition. It has more to do with how your startup has evolved. Once it has reached a certain level of product-market fit…that is when you can transition to more data-driven decision making,” he says. 

Gaurav Ranjan, VP of Investments at Prime Venture Partners [Image Credit: LinkedIn]

Operating metrics vs fundraising metrics

But before moving towards deriving decisions based on metrics, it is important to choose the right metrics your startup needs at that given stage.

Simply put, you need to look at two things while choosing the right metrics for your startup: Can they predict the health of your business? Will they change the way you operate? 

Once you have landed upon metrics that fit your startup, it is necessary to understand the difference between operating metrics and fundraising metrics.

Gaurav says operating metrics are necessary to track the day-to-day workings, optimise them, and help you move in the right direction. Meanwhile, fundraising metrics are something an investor would look at and judge your business.   

 “Broadly, investors would look at your month-on-month growth, revenue, users, your CAC, LTV. Whereas with your operating metrics, your product manager, for example, may look at the way your customers are adopting the product, the way they’re using different features, and so on and so forth.” 

The business model is important while tracking metrics. For example, if you're a marketplace, you would want to track the LTV on the platform. A SaaS business, however, would want to track CAC payback period, churn, etc. 

Draw actionable insights

After settling on the metrics depending on your startup stage or sector, it is important to know how to draw actionable insights from metrics.

“One of the common mistakes people make is looking at high level metrics without understanding how that metric was arrived upon or what are the underlying data points for that metric?” Gaurav says. 

He explains it further with the example of churn metrics. Say, you sign only a one-year contract and then track your quarterly churn, it will be very low. The right way to track churn is by the number of users who moved out, divided by the number of users who were up for renewal. 

Many people track quarterly or monthly churn without knowing when their contract cycle expires. It may happen that when the churn turns out to be low, at the end of the year you may see about 50% of customers have churned. But in some cases, it may so happen that even after losing 50% customers, the remaining 50% stays back and the net revenue retention from them outstrips your customer churn.

This means that the customers retained on the platform are actually seeing the value in the platform, and that is the right TG for you to go after. The customer who churned may not be the right TG.

"So it becomes very important to track underlying data within a metric, try to understand how a metric is derived from the underlying data, and not get fooled by metrics,” Gaurav says.

To hear more, listen to the podcast here

Edited by Teja Lele Desai

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