Tomasz Framski

Omnichannel Banking Expert & Co-Founder
Tomasz Framski

Omnichannel w bankowo┼Ťci to moja pasja, kt├│r─ů realizuj─Ö ka┼╝dego dnia, wsp├│┼étworz─ůc Consdata.

Wierz─Ö w czynnik ÔÇ×WOWÔÇŁ w bankowo┼Ťci. Uwa┼╝am, ┼╝e banki powinny zawsze zaskakiwa─ç swoich klient├│w innowacyjnymi rozwi─ůzaniami obs┼éugiwanymi nie tylko w spos├│b efektywny, ale i atrakcyjny.

Mam szcz─Ö┼Ťcie, ┼╝e mog─Ö zmienia─ç bankowo┼Ť─ç na lepsz─ů i widzie─ç, jak ludzie korzystaj─ů z niej na co dzie┼ä.

Omnichannel Banking is my passion, which I pursue every day co-creating Consdata.

I believe in the wow factor in banking. I believe that banks should always surprise their customers with innovative solutions served not just in effective, but also attractive way.

I feel lucky being able to change banking for better and see people use it every day.

How can we measure the effectiveness of electronic applications?

(Reading time: 3 - 5 minutes)

While presenting the Eximee Platform to our customers, we often ask them about their experiences with electronic applications. We specifically ask them about what types of applications they share, on what devices and in which channels. One of our secondary questions is about the average conversion rates from application forms. From our perspective the answer to this question is key, as it indicates the customerÔÇÖs level of technological and business advancement. The answers are usually evasive and sometimes even surprising. I remember one in particular:

Consdata: What is your average conversion rate on sales applications?
Customer: Almost 100%
Consdata: How did you manage to achieve that? That is a very good conversion. What solutions are you using?
Customer: ItÔÇÖs simple, we process almost all the applications our customers submit.
Consdata: I see, but we are more interested in how many customers do not submit the application, even though they start it...
Customer: Hmmmm, we are not interested in them...

While this is an extreme example, many customers measure conversion and then only come to us when they want to improve it.

General KPI

We have picked out a few, very important indicators. These will allow you to quickly learn something about our computer-based applications.

Conversion rates

This tells us how many customers have completed the application process (e.g., a 20% conversion means that one in five customers complete the process, while the remaining four do not). Based on our many years of experience we can say that:

Conversion Comments
 up to 25%   there is a lot to improve
 25% to 50%   there is room for improvement
 over 50%  there is no point improving the application 

Channels for submitting applications

Very important to understanding how our customers perceive what we offer is the relation between conversion rate and the application submission channel:

    Desktop     Mobile  
 Conversion  47% 2%

The above example shows that our desktop application is very good, so why is our mobile channel performing so poorly? We observe that people often create a single application form to serve both their desktop and mobile channels. The result can be seen in the example above: almost no conversions on mobile devices. It helps if we distinguish what we offer in each channel. For example, the desktop channel might allow applications for cash loans of up to PLN 100,000, but only by following the full path. The mobile channel may have a simplified path, but also a credit limit of PLN 5,000. Such a solution can efficiently improve conversion rates in our mobile channel.

Distribution of system load

 Time of day    Share %  
0-3 1%
3-6 5% 
6-9 22%
9-12 20%
12-15 8% 
15-18 10% 
18-21 18%
21-0 16%

Information about the time of day when our customers complete an application form is crucial when deciding to purchase media. Knowing the days and times when an advert goes out allows us, for example, to analyse whether it directly affects customer purchasing decisions, what conversion rates can be achieved through specific media and so on.

These KPIs indicate generally how many customers we are losing, and why. More detailed information is provided by the specific indicators presented below.

Detailed KPI

By analysing the KPIs, we try to answer the question we raised at the beginning: why do 4 out of every 5 customers leave our store without going to the checkout?

Last visited element

The last visited element is a key piece of information about our would-be customers. This is where we discover where in the application form they chose to leave, and even on which element. This helps us to understand what discourages our customers from continuing. For example, it may be the "Current vehicle mileage" field, as people often do not have this information to hand when filling out their application, so they have to stop. In such a situation we can allow the customer to save the application, and then remind them to return at a time more convenient. We could also drop the field, but that would be a business decision, although one now easier to make as it is based on a solid argument ÔÇô conversions.

Average time spent on an element

It is very important to monitor how long it takes to complete an application form. The time spent on any given page or element translates into conversion rates. This KPI provides us with information about which pages and elements in the application are the most problematic for our customers. Finding the most time-consuming field, from the perspective of the customer, can improve the usability of the form. A good example is the PKD field, where we have to select the right code. Implementing a text search in this field, instead of a selection tree, can save time for our customer.

Summary

By observing our customers, we see how much effort they need to complete our online form. Unfortunately, this is only the first step in creating a good offer, but one where many customers stop, for various reasons. Primarily there is a lack of information on the changes required (lack of KPI) and, secondly, because of the high cost of introducing the necessary changes to the application. The Eximee Platform solves both problems. If you want to know more, contact us.

1 For the purpose of this entry, and for simplicity, we assumed that the average conversion in a retail store is similar to an online one


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