How Knab multiplied the number of fee-paying customers by ten within one year

 

Knab was founded in 2012 on the belief that things had to change in the financial world. Therefore an innovative online bank with a fixed price proposition was introduced. The expected traction from the market, however, did not take place in the first 1.5 years since going live. To make a change Knab transformed in 2014 to an organization driven by the power of Data Analytics. As a result the weekly net growth accelerated exponentially and the number of fee-paying customers multiplied by ten within only one year.

 

 

“Knab was founded in 2012 because we believe that our customers will become more and more responsible for their own financial position.”

René Frijters, founder and director Knab

 

In January 2015 the Knab service desk is overloaded with consumers that want to become customer. On Twitter happy customers share their experience with the excellent Knab service and its innovative products. And the Dutch media is writing about the ‘golden interest rate award’ that Knab received for its interest rate policy.

How different was the situation one year before: the same innovative products and excellent service but only a few thousand customers to experience it. This contrast was achieved by harnessing the power of Data Analytics in cooperation with MIcompany.

 

Build a longitudinal view on customers and prospects

To be able to make impact with Data Analytics we started to build a longitudinal view on the Knab customers and prospects. With a longitudinal view we can follow each individual customer through time. We make, so to speak, a movie of every customer by using pictures of frequent moments of his customer journey.

Since the introduction of the longitudinal view it was possible to deepen the weekly net growth to relevant customer flows. In this way the development of the net growth of fee-paying customers can be better understood. We could, for example, explain why a specific month had a notable low net growth: not because the gross inflow was low but because the outflow was extremely high. Due to that insight we knew we had to focus on outflow and that inflow was not the problem.

An additional benefit of the longitudinal view is that we can also identify the customers in each customer flow. In the above example, we were able to look at the individual customers who left Knab in that particular month. This peak turned out to be caused by customers acquired by one specific channel while the other customers showed a stable outflow percentage. These kinds of analyses formed the basis for decisions to increase or reduce the efforts put into specific inflow channels.

 

Determine growth levers & customer insights

By further analyzing the customer flows we were able to improve them. As for most start-ups the most important growth lever was of course inflow. Knab increased the inflow by improving their proposition based on quantitative customer research, described in the next paragraph. But we also identified other important growth levers, of which we will give two examples:

• Reducing the outflow based on cohort analyses
• Increasing the upsell to paid products based on a test-learn-improve cycle

At the start of 2014 the scoreboard showed that the outflow in the first 3 months was extremely high for one of the products. Over 30% of the customers left Knab or downgraded to a free product. With cohort analyses the timing of the outflow could be identified: what is the moment of outflow relative to the moment of inflow? It turned out that an outflow of 20% coincided with communication about the end of the free trial period. Modifications of this communication resulted in a decrease of the outflow to only 5% after this communication. By monitoring the outflow percentage in the weekly Knab scoreboard, Knab was able to directly react when the outflow of a specific product or specific customer group increased again. In the second half of 2014 the Knab scoreboard showed that the percentage of customers of the free product that upselled to a paid product dropped extremely. Analyses showed that the decrease in upsell was the consequence of less focus on this topic within the sales department.

 

 

 

“At the end of 2013 we needed a complete commercial relaunch. To create commercial success the scoreboard was essential.”

Frits Drost, Chief Commercial Officer Knab

 

Together with the sales department we set up a detailed test-learn-improve cycle. In this process we tested different messages, channels, timings and customer profiles to find the optimal combination that creates the highest upsell. Together with the weekly sales report, on both team and individual level, this resulted in a significant increase of the upsell: both the number of customer reached and the conversion on reached customers more than doubled. In this process control groups were essential: we could only determine the uplift of different approaches if we also knew the behavior of comparable customers that we didn’t approach, the so-called autonomous effect.

 

 

Strengthen the proposition based on quantitative customer research

Until the start of 2014 the Knab positioning was mainly focused on the vision of Knab. Concrete benefits for the customer did not occur in most communication. To reveal possibilities to increase the customer inflow we executed a quantitative customer research. This research showed in the first place that concrete benefits are crucial to get the attention of potential customers: the proposition ‘double interest’ was indicated as the most attractive 8 times as often as the original positioning. The research also confirmed that many consumers are anxious about switching to another bank. 35% of the respondents indicated to fear the fact that they have to inform authorities and relations and 34% fear the administrative burden. Also 17% admitted they were not sure what is involved in switching to another bank. This was in sharp contrast with the experiences of consumers who recently switched to another bank: 48% of this group did not encounter any problems in the process of switching.

 

 

Based on these results Knab decided to increase the publicity around the existing Knab interbank switching service to take away the consumers obstacles. This service settles the switch with only one signature. The service was used more prominent in their communication and was combined with a €50,- incentive to encourage the use of the service. The research also revealed that consumers heavily underestimate the cost they pay at their current bank. 39% of the consumers answered they did not know what they paid and 38% thought they pay less than €3,- a month. As a result, 40% of those who were interested in the Knab proposition dropped out at the moment the monthly fee was shown. Therefore Knab chose to make consumers more price conscious with an online profit calculator. This calculator shows which Dutch bank is the most attractive, including both cost and interest, based on the personal situation of a consumer. The calculator increased the conversion of prospects on the website with 60%.

 

Identify opportunities & roll out initiatives

Since the introduction of Data Analytics at Knab, we identified different opportunities and rolled out several initiatives based on analyses. As an illustration we will describe two of the initiatives executed in 2014:

• An introduction program based on in depth customer insights
• The introduction of the business product based on the quantitative customer research

At the start of 2014 around 30% of the customers did not use any of the Knab products or services. This was not in line with Knab’s purpose of financial conscious customers. Therefore Knab introduced an introduction program to activate new customers. As a result the percentage of inactive customers decreased to 10% begin 2015. The realization of this program was based on customer insights made possible by the longitudinal customer view. Three key ingredients made this program successful:

• offered products and services;
• order of offered products and services;
• timing of the program.

To determine which products and services Knab should offer in the program we analyzed which products and services led to the most loyal customers. Customers with balance and activity on their current account showed a significant lower outflow than customers without current balance or activity. Therefore the use of the current account got a prominent place in the activation program.

Also the order in which customer activate the different products and services was important: it turned out that most customers started with a savings account before they became active on their current account. To reduce barriers the program started with suggesting a savings account followed by information about the current account to really activate customers. The last key ingredient was the timing of the program. Analyses showed that active customers became active really short after the moment of inflow. After two weeks only 25% of the customers could be activated and after 6 weeks this was only 10%. So it was really important to execute the activation short after inflow. This resulted in an intensive introduction program in the first weeks after inflow.

 

“Data Analytics helps us on a daily basis to make the right decisions and focus on what to work on.”

Leslie Hogeveen, Head of (Digital) Marketing & E-commerce Knab

 

 

 

From the start Knab focused on the consumer market. At the start of 2014 Knab considered to introduce a product for the business market, focusing on small businesses. The quantitative customer research showed that this direction could be a real opportunity: almost 20% of the respondents from the small business market considered to switch to another bank in the past year. Even 8% of the business respondents were (very) dissatisfied about their current bank, among consumers this percentage was only 4%. The research also learned us that the optimal approach of the business market differs from that of consumers: business prospects were more sensitive for the low cost instead of high interest. The introduction of a product for the business market in May 2014 proved to be a great success. The online conversion of business prospects was twice as high as the conversion of consumers and the inflow was on a consistently high level from launch. At the end of 2014 over 40% of the fee-paying customers were customers from the business market.

 

Building analytical capabilities

After the success in 2014 Knab was ready for the next step: further developing their in-house analytical capabilities. We improved this capability along three axes:

 

People & organization

To secure the knowledge on Data Analytics Knab hired several analysts in 2015. Most of these analysts are educated in the Aegon Analytical Academy facilitated by the MIacademy. Together we deployed an intensive transition period, to transfer all acquired knowledge about Data Analytics at Knab. But not only the analysts were involved in developing the analytical capabilities within Knab. One of the success factors was to involve a wide selection of employees from the organization. Both Management, Marketing, Product development, Sales, Service and Finance participated in action learnings on data building, campaign evaluation, story lining and visualization.

 

Data & tooling

To enable Knab to continue harnessing the power of Data Analytics, we implemented the Banking Analytical Suite (BAS) at Knab. The BAS is a standardized MIcompany technology solution fit to the specific needs of Knab. The solution is based on the longitudinal customer view and consists of three components designed for all layers within the organization.

• Standardized insights: automated and interactive weekly insights on the most important KPI’s, customer flows and activity measures.
• Data exploration: interactive tooling to deepen the standardized insights without knowledge on programming.
• Analyses database: integrated longitudinal customer view for executing in depth analyses.

“If you really want to be customer centric and create a unique customer experience, you have to implement Data Analytics.”
René Frijters, founder and director Knab

Models & metrics

Where Knab had to focus on volume targets in 2014, it becomes more and more important to steer on value targets. For this purpose we developed a customer lifetime value metric. This metric expresses the value of each individual customer during the rest of their lifetime at Knab. The metric enables Knab to retain the most valuable customers, focus their sales activities on creating value, and target the right prospects. Analysts, Management, Marketing, Product development, Sales, Service and Finance got trained to work with the metric.

 

 

 

 

 

Laura Brandwacht, Senior Analyst – MIcompany

Marnix Bügel, Managing Partner – MIcompany

Frits Drost, Chief Commercial Officer – Knab

Leslie Hogeveen, Head of (Digital) Marketing & E-Commerce – Knab