Banks have been around for hundreds of years, but the internet has only exploded in the last 30 or so. The intersection of these storied institutions with new technology can be fraught with obstacles. What is optimization for banks? Some customers will always want to do their banking in person, but more and more are converting to online banking options (as many as 36% of Gen Y users, according to this a study by Accenture).
What is optimization for banks, and how do you optimize your website to best serve both customers and your business goals?
Effective Experiments interviewed digital optimization experts from SunTrust Bank and The Cooperative Bank to discuss how they handle their optimization challenges with financial sites and what their biggest learnings are.
We asked our three experts these questions:
What are the most challenging parts of optimization for banks?
“Generally speaking, I’ve found one of the most overlooked and challenging parts of optimization is finding the correct problem to solve.
In order to solve the correct problem, you need to be able to understand what a visitor to a website is trying to do and what is obstructing them from completing that task. Data will help uncover the visitor’s motivation and what they are trying to accomplish.
However, this is where it can get challenging for banks as you are dealing with people who have very different motivations. For example, someone coming to the website looking for a savings account is going to behave differently than someone who is looking to apply for a loan or a current customer who wants to view their checking account balance.
Because of this, you need to be able to dig deeper into the data and only look at data that pertains to the area of focus.
Let’s use the checking page as an example and assume we have seen a decrease in checking accounts opened over the last month. The data shows the conversion rate has lowered from 3% to 2% and the amount of traffic has remained the same.
On first glance, we could assume the page is now underperforming. However, when you remove people who only come to the checking page to login to their account, we find the conversion rate is actually 5% and traffic has decreased.
Further data discovery could show the underlying problem was actually people having trouble navigating to the checking page.
This is somewhat of a simple example but highlights how different people’s motivations coming to a bank’s website could skew data. Analyzing data at a deeper level will allow you to better understand what the actual problem is.
Another challenge of optimizing banking websites has to do with the varying products offered. (This directly contributes to the first challenge mentioned of having different motivations to understand.)
This can make traditional CRO and A/B testing very difficult. For example, let’s say we finished running an A/B test and the treatment increased conversion rate by 5%. On the surface, this seems to be a winning experience.
However, the 5% increase largely came from more savings products being opened at the expense of fewer credit cards being applied for. We actually created a losing experience since credit cards are more profitable for the bank than a savings account.
You need to be able to understand the balance between increasing volume and quality of accounts as well as the profitability of each. A good exercise to help overcome this is understanding how many savings accounts 1 credit card is worth.”
How have you approached these challenges? What advice would you give to someone just starting out, knowing what you know now?
“My advice would be to learn how to pull and analyze data or work with someone who does. Always ask questions that will allow you to dig deeper into the data to get a better understanding of what it is telling you.
Try to get as specific as possible when looking at a set of data and be sure it is for the specific task/goal you are optimizing for. The more data you have and the better you understand it, the better chance you have of understanding what people’s motivations are and what the real problems are.
Having too much data hasn’t hurt anything, but not having enough data can lead to misinformed decisions.”
What are the most challenging parts of optimization for banks?
“Conversion rate optimization can be complex, especially with the staggering amount of data that most companies have at their disposal. This data can create situations where leaders, who have been successful based primarily on their personal experiences, may find data that challenges these experiences.
While this data does not always contradict the subjective opinion, it is a more empirical indicator of the environment and a better basis to make decisions.
I have found that the best leaders are very comfortable with recommendations based on metrics, even if they don’t necessarily align with their own intuition.
Another challenge is parsing testing ideas into valid tests. See if this sounds familiar, “I bet if we changed the color of the button we’d get more sales” (or something to that effect). While it may, getting to what we test involves careful methodology which may not result in this particular strategy.
For example, if the issue were a drop in sales, we would start with an analysis of what might have changed to cause the drop. (Did we lose traffic? Did our prices go up? Did our competitors advertise more heavily? And so on.)
Only after we had a direction to pursue would we design a test. It’s challenging because as testing professionals, we live and die by the data which doesn’t support every testing idea we receive.”
How have you approached these challenges, and what advice would you give to someone just starting out, knowing what you know now?
“In college, statistics and quantitative methods of business were not terribly exciting. Today, they are an integral component of CRO success.
Mastery of data and the ability to connect cause and effect will provide you with a unique and marketable skill set. Truly successful marketers know how to make a business case using metrics and generate results through testing.
And while you may have the facts, remember that you are still working with people whose opinions and experiences may not align with the data. Be confident – and flexible – and learn how to succeed through solid testing principles and the credibility it brings.”
What are the most challenging parts of optimization for banks?
How have you approached these challenges, and what advice would you give to someone just starting out, knowing what you know now?
Robert Martin says his two biggest challenges in optimization for banks are:
His 3 biggest lessons are:
David Bacon says the two biggest challenges in optimization for banks are:
And his 3 biggest lessons have been:
Becky Franks says her three biggest challenges in optimization for banks are:
Her 4 biggest lessons are:
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