05. 16. 2018
Are third-party tools really a godsend for digital banking sales?
Teaming up with a third-party provider can work wonders for banks seeking to pump up digital sales and sweeten the customer experience at the same time. You have to see it to believe it: check the actual sales results, KPIs and a short use case from a commercial lender.
More and more banks are warming to third-party digital sales and engagement tools to optimize sales opportunities and successfully compete with challenger banks and tech giants. Especially, if they’re looking for ways to create relevant, personal and timely interactions with clients.
How do these tools work in practice, you ask?
First, they collect and merge traditional and non-traditional banking data to better understand customers’ behavioural patterns, and to boost digital conversion rates and profitability for products. What kind of non-traditional data are we talking about? Think social media activities, information from mobile devices, geo-location parameters and even weather updates.
Next up is decoding all this information. Based on the decoded signals, banks can offer clients relevant products and services after mapping out customers’ habits or life events. “Customers today expect banks to be there for them at the right moment in their lives, for example, when they’re starting a family, going to uni or moving to a new house,” W.UP’s Director of International Sales and Business Development, Tamás Braun, explained.
Insight-driven tools for the win
W.UP helps financial institutions revitalize customer interactions by pinning down key moments in their customers’ life and turning them into next-level financial experiences. To make this happen, Sales.UP, our insight-driven sales and engagement tool merges behavioural data, advanced analytics, and pre-built and ready-to-use customer insights. The software creates a balance between customer care, advice and sales messages – and bids farewell to the good ol’ direct sales push, which simply doesn’t work anymore.
Pre-built insights in Sales.UP use machine learning and predictive analytics to follow every step of a customer’s life, for example, if they’re planning to buy a house. Algorithms not only analyse their account balance, but also use non-traditional datasets like location, mobile device data and other data sources. When mobile data is married with transactional data, you can go even deeper and see information about their shopping habits or holidays, and even visualize it on a map.
Third-party solutions, like Sales.UP, also help measure the effectiveness of these insights, mostly by tracking the actual conversion of leads into sales. This information, in turn, is used to fine-tune these tools and improve their results. Sales and engagement software can also perk up the quality of lead data, lower the number of unusable leads, and decrease undesired sales contacts or pitches to avoid eroding customer relationships.
Implementation use case: what are the quick wins?
Sales.UP has already been implemented by MKB Bank, a mid-sized financial institution in Hungary, working towards more meaningful customer interactions. “Customers go through life events, they have fears and desires, and each and every one of them needs a unique solution,” MKB Bank’s Data Asset Management and CRM Director Attila Kezdődy said at W.UP’s recent webinar on digital banking sales. “Customers don’t want products, they want solutions,” he added.
MKB Bank uses both traditional and new sources of data to better serve clients during various life stages. However, not all life events can be captured by a bank, and these events must be carefully combined with real-time activities. For example, the bank knows the customer’s balance and that they are travelling by plane so it can be assumed that the client may need an emergency cash loan (as people travelling abroad normally spend more than usual).
“We need to be aware of the client’s goals, wishes and feelings so we can set up the right services and right messages,” he said. “Getting it right means that the client will be happy to be involved with us and this is the time when we can create value for them,” Kezdődy explained.
MKB Bank had been looking for a strategic partner to assess what services and offers would be relevant for its customers and to come up with the right ideas, technical solutions and workarounds. W.UP’s analytics team helped the bank build the location database as well as categorize and segment customers. “This was a milestone on our journey towards getting it right for the very first time,” Kezdődy added. “Ultimately, it’s the merge of fintech solutions and learning from other players, like Google or Amazon, that can help banks use their collected data better,” he said.
It all adds up: sales results and KPIs
Sounds too good to be true? Let’s see how third party tools, like Sales.UP, actually affect digital banking sales volumes and profitability. The following tables with actual banking data show the improvements in key performance indicators (KPIs) for selected products as a result of using Sales.UP.
Additional income is partially calculated based on the actual average conversion rates of specific banks (as-is data). Interests, fees and commissions used in the calculations for each product are actual averages of specific banks. Banks, however, may include different expenses in their cost calculations of banking products so conversion rates of individual banks may significantly differ.
As you can see, conversion rates have gone up by 2.14-2.4 percentage points while transaction numbers have doubled for overdrafts, credit cards and personal loans, which all generate additional income. Sales tools such as W.UP’s Sales.UP work best for banking products where all workflows and processes are already digitalised but they can also bring great results for products that aren’t there yet.
Missed our webinar on digital banking sales? Catch up here and listen to the on-demand webinar.
If you’d like to know more about how banks can compete with new competitors, check out W.UP’s latest white paper about digital sales best practices in banking.