Single metrics for different product startups

The world is now startup frenzied. The very joy of solving a problem has enticed the best of minds. Whatever the industry might be, if you have a problem it is looked at as an opportunity for the next startup to solve. Hence, the world we live in is not cradled with problems, it is full of opportunities.

However, as anyone would tell you startups are not easy. All you have is an idea and the confidence to execute it. Hence, many fail to even take off. Others lose out on the wantonness of the demanding journey. One of the major reasons for the latter is failure to measure the effectiveness of efforts. Since the problems startups solve are unique, it poses a great challenge for founders to stay focussed and take failure and success in their stride. Most importantly, they must know where they have faltered, and data is the answer to all questions.

The two-word definition of success of any startup is Self Sustenance, however far-fetched that might be. For most startups in India, it is still a mirage. Hence, in this race for supremacy and growth, number crunching has become the order of the day. I believe if measured correctly, the right data can be a true reflection of efforts. But data can get overwhelming. I have always believed that data is the harsh version of a reality check. However, many focus on irrelevant data and go down the path of self destruction.

The metrics used to measure data are numerous: number of sign ups, daily active users, monthly active users, quick ratios, activation rate, revenue, the number of transactions, gross merchandise value (GMV), recurring revenue ratios, revenue growth numbers, daily traffic etc. It is about choosing the right metric for a product.

Different startups use different metrics to measure their performance. Most successful startups succeed in identifying the right product metric. For instance, e-commerce platforms, for quite obvious reasons, would focus on the number of transactions. If a similar metric is used by a startup whose domain lies in e-commerce, then the probability of failing in the long run would increase. A social network based startup would measure itself on the basis of user engagement, while a content-based firm would analyse the number of page views.

These are some of the most commonly used metrics today to measure the level of success in a competitive environment. But should these be the only metrics that startups use? The answer definitely is no. So, doesn't that belie the entire piece? No. The metrics that startups employ depend on the business they are in, as mentioned below:

Transactional (B2C): The metrics should change depending on what the stage the startup is at. For example, the same e-commerce company must concentrate on the revenue generated once they have sorted out the daily transaction count.

Transactional (B2B): Businesses use a number of metrics to measure their performance at different phases to see whether they are on the right track. These can range from the number of newsletter sign ups at the inception stage to the number of successful sign ups or orders at the growth phase to the number of repeat orders at the consolidation stage.

Content based (single user): For content-based firms like Daily Hunt, Flipboard or Feedly, the metric used would be the amount of time spent on the product, which needs to be a quintessential part of a user's daily life.

Content based (network): For a social networking startup, the key metric will change from time to time. When starting out, firms should give importance to the acquisition rate to reach a threshold of users. Once the platform achieves a respectable number of users, the metric should then focus on user engagement. This can be measured in terms of monthly active users (MAU), weekly active users (WAU), daily active users (DAU) and hourly active users (HAU). For a growth stage social network, DAU is the metric that should come to the fore.

Startups manage a tonne of data, and when analysing metrics, sometimes irrelevant data is crunched. This is where most startups fumble. Data is meant to serve as a reality check for start-ups. If used wisely, data can do wonders but there have been numerous instances where scanning data beyond a certain level proved to be catastrophic for the company. Thus, companies should avoid falling into the data trap and protect themselves from vanity metrics.

An alumnus of IIT Delhi, Mudit Vijayvergiya is co-founder and director at Curofy, a networking platform for doctors.