I think setting up consistent metrics makes all the difference in relation to the lean startup model thinking. The practice of creating Minimum Viable Products is becoming a prevalent way to create new products and services. But in order to keep on improving our MVPs, it is essential to figure out the relevant metrics in relation to the customer’s overall happiness and satisfaction with the product or service.
So let’s take a brief look at the lean methodology in relation to metrics. In a recent post entitled “Flow and Seductive Interactions” (https://iiriskblog.wordpress.com/2016/03/14/flow-and-seductive-interactions/), I emphasized the need to create products and services that cater for the customer’s personal improvement, while giving us a sense of a true “flow experience” of micro-moments while performing relatively complex tasks. This is essential especially in multichannel digital service design.
But how to measure all of this?
Eric Ries, the author of “The Lean Startup”, says that while we certainly need figures, the customers are individuals.
In his book, Ries states that “Numbers tell a compelling story, but I always remind entrepreneurs that metrics are people, too. No matter how many intermediaries lie between a company and its customers, at the end of the day, customers are breathing, thinking, buying individuals. Their behavior is measurable and changeable.”
I agree with Ries. So essentially, we need to figure out what works, and also understand why it works. Focusing on these questions, especially the “why” part, helps us choose the correct metrics.
In “The Lean Startup”, Ries states that in order to support the Build-Measure-Learn feedback loop, the metrics need to be “Actionable, Accessible and Auditable”.
First of all, let’s take a look at “Actionable” metrics.
Your company may attract 1 000 000 unique visitors to its website annually. However, this figure might not be as relevant as many people think. As Ries explains, “For a report to be considered actionable, it must demonstrate clear cause and effect. Otherwise, it is a vanity metric.” So the question we need to ask next is, where are the visitors coming from and why? And follow up by setting the metrics for that.
Ries also provocatively states that “All too many reports are not understood by the employees and managers who are supposed to use them to guide their decision making.” Furthermore, he says that “Unfortunately, most managers do not respond to this complexity by working hand in hand with the data warehousing team to simplify the reports so that they can understand them better.” I think this is true.
Based on my own experience, this might be one of the most important issues to solve in relation to metrics. I think setting up an accessible dashboard of the most relevant metrics should be a top priority in the analytics team. There is currently a plethora of excellent analytics dashboard software available. I personally prefer the kind that are accessible for any employee at any time, modular and visual.
Finally, Ries states that all analytics and metrics must be “Auditable”. An easy way to test hypotheses based on analytics is to interview the people that are using the product or service. Another feasible way to audit and validate the hypotheses is A/B testing. Playing around with various landing pages, for example, usually certainly pays off. Checking out the heatmaps of the existing websites also helps. Yet another practical way to test the hypotheses based on metrics is creating traffic via modifying the parameters of search engine optimization. I think regular auditing paves the way for regular improvements.
So the KPIs as well as other metrics should have a clear relation to the overall customer experience as well as the strategic goals of the company. Some of the most important KPIs still remain social media audience size, reach, engagement rate, website traffic, and the amount of leads and conversions. But understanding why visitors end up on our social media or landing page, and why they convert into customers is essential in order to create the next MVP as well as improve on the multichannel experience of the existing ones.
Setting up the most relevant metrics for these processes should be a top priority in the analytics team as well as in the C-suite.