Interview with Max Rast, founder of Klar, eCom Unity Live sponsor

On April 13 the company will host eCom Unity Live, an online event for e-commerce players that will examine the state of the e-commerce market, and how to get the most relevant insights from the data available. In this interview with Kolsquare, which is a sponsor of eCom Unity Live, Klar founder Max Rast explains why Klar is relevant for brands combining e-commerce and influencer marketing.

How did the idea for Klar come about?

I wanted to make something easy, equivalent to Shopify or Klavio, but on the data side of the business. Something that’s easy to set up, quick, easy to maintain, affordable, but also gives me flexibility and customizability in the right places while allowing me to dive deep into the data. Something that combines the three core growth levers of an e-commerce company: acquisition, retention and financials. Klar gives you the power of an internal team of five, six people at a fraction of the cost and much quicker.

It’s a time saver because you don’t have to spend time creating your own reports. We give you a lot more insight into your data than an e-commerce brand doing less than €50m could do themselves, because they simply don’t have the resources to hire a five or six person team. Most of our clients are in the range of €1m to €50m ARR.

What are the strategic challenges that you’re helping them to solve?

Every brand’s data and situation is unique. The classic case is really understanding what marketing channels drive performance and efficiency in the short term — revenue — but then also broken down to a profitability level, and again even further to the lifetime value of a customer. The integration of where do I spend money, what quality of customers do I acquire, and how much profit do I generate from them over the longest period of time; bringing it all together, that’s where the juice lies.

For e-commerce marketers, are there specific channels and platforms that are more relevant than others?

There is a very clear hierarchy within e-commerce brands. Number one is usually Facebook. Number two is Google. Number three is influencer and number four is TikTok. This may vary from brand to brand. Some brands are more Google heavy because there’s existing search demand.

We literally collect and measure everything. It starts with obvious short-term metrics like revenue return on ad spend, new customers, customer acquisition costs, etc. But we can go quite a few levels deeper. We can tell you how many existing customers churned and were inactive. Did a particular influencer reactivate those customers: because new customers are cool but reactivated customers are often overlooked but are super valuable.

We can also look at the lifetime value [of the customers] each influencer brings in. [It’s possible to have] four to five times the difference in the lifetime value depending on which influencer brought that person in.

We can go on a more macro level when it comes to developing your playbooks to analyze performance based on the platform where the influencer posted, the niche the influencer or content falls into. You can look at whether you see decreasing performance over time if you keep working with the same influencer.

If you wait less than 30 days between partnerships with the same person, do you have a drop in performance? If so, you should pace your continuous partnerships increments every 45 days instead of every 20 days.

How should brands tackle the proliferation of data without getting submerged by it?

Looking at it too much can lead to inaction just because you might get different indications on different data points. It’s always important to really understand your business, where you’re at and what you’re optimizing for. Then narrow it down to one or two numbers. So find your North Star and optimize for that. But then obviously you want to have the ability to go deeper to find second order effects or correlations that might have an impact. You probably want to steer your marketing towards one or two numbers — a performance metric and a control metric — because you can always fake numbers; it’s easy to have good efficiency if I don’t spend a lot, for example.