Over the past week, I have reached out to many of my banking industry colleagues in the U.S. and abroad asking for examples of where 'big data' is being used effectively in retail banking.
The response was underwhelming to say the least, as the majority of banking leaders provided examples of 'works in progress' or 'initial wins', with some of the most mentioned case studies being in the areas of risk and fraud prevention as opposed to marketing.
In addition to a post on big data by Aite Group's Ron Shevlin on The Financial Brand, and widely covered discussions about 'big data hype' on blogs from Gartner and CapGemini this past week, most industry leaders believe banks need to focus on data close to home before expanding their pursuit of the next shiny object. To this end, a friend from the U.K. offered to provide a guest post on the topic from his perspective as a supplier to the financial services industry.
By Darren Oddie, CEO and co-founder of AGILEci
Consumer banking behavior is changing rapidly before our eyes. Will this changing consumer behavior mean that incumbent retail banking 'zombies' may become corpses walking the halls of banking, as energizing and engaging competitors take enlightened customers away from them?
I firmly believe that many retail bankers are operating on autopilot in an increasingly dynamic and complex environment. They are trying to understand, develop, deliver and manage new solutions with buzzwords such as cloud, big data, mobile, social, NFC and mobile wallets to name a few.
I'm going to highlight one of these trending terms within the context of retail bank marketing, and the mots de jour are 'big data'.
We hear it, we allegedly see it, but we can't touch it. We can't touch it because we don't know what 'it' is. There are official and unofficial definitions of big data mostly distributed by vendors who want to sell a 'solution' to the industry. 'It's big', 'It's fast', 'It's varied', 'It's unstructured', 'It's social', 'It's not technology', 'It's data programming', 'It's a process', 'It's statistics', 'It's analytics', 'It's hype', 'It's bullshit' . . . and so on.
If a bank were truly using big data, bank marketers would be engaging customers in ways that were unforeseen only a few years ago and their technologies would enable this. Retail banking would be operating faster than the speed of changing customer behaviors, similar to the post a couple weeks ago on this site written by Scott Bales from Movenbank entitled, 'Finding Serendipity in Big Data'.
Full digitization of financial services offerings would be available to the majority of customers and the bank would be in constant omni-channel dialogue with their customers to self-individualize their chosen offerings as shown in the illustration below. Those who wanted physical interactions would be able to have physical units. Those who wanted digital could have digital. Those who wanted everything, well . . . they could have everything. This wouldn't be an issue for banks, as their technology would be agile enough to individualize every interaction and every offering.
Customers would have adopted their physical modus operandi because it would be truly self-personalized, cheaper, with much better service and with richer benefits. The automated banking service would encompass full and transparent management of personal and business finances, within the personalized context of the individual customer (not the customer group).
Much of the big data use to date has been around risk monitoring and fraud control. Bank marketing big data examples that are currently expounded tend to rely on using data for customer engagement and satisfaction. 'We'll send you an individualized statement of your account', 'We''ll ping you with an offer as you walk past your favorite store' and 'Access personalized offers online, via mobile or at the point of sale' are not examples of big data in action. They are examples of taking structured and/or unstructured data, analyzing it and using it for marketing purposes.
Data may be pulled from disparate sources and targeted at a customer, however, it's unlikely that this communication is truly at an individual level, real-time automated and as sophisticated as payment scheme processing, authorizations and risk/fraud management is today. The day that a retail bank's marketing infrastructure is fully data integrated and as sophisticated as a payment scheme's processing infrastructure is the day that I believe big data is well and alive in retail bank marketing.
Individualized engagement and dialogue to create self-personalized products is my idea of applied big data. It's not just about real-time, 1:1 push and pull marketing. Retail bank marketers need to realize that they are operating at a speed that is slower than the changing behaviors of their customers. The more they talk about big data and don't deliver the way other industries are delivering, the further away from the reality of truly next generation products and engagement they will be.
The consumer is becoming more aware of what is possible with today's insight and computing capabilities, while retail bankers are looking more like zombies, bereft of consciousness yet able to barely respond to surrounding stimuli.
Non-Bank Big Data Examples
Let's take a look at two companies that retail bank marketers can learn from.
Borders Group, Inc. and Blockbuster are great examples of companies that failed to keep up with the digitization of consumer behavior. Once seen as the corporate face of physical sales on main street, they battled for survival and then collapsed. They went from market dominance to death, in a relatively short time, with no strategic reinventions. They are the most cited, but by no means the first or last case studies that could be used.
Conversely, Amazon and Apple grew from nothing to prominence in digital sales globally (books and music among other things) in a relatively short period of time in comparison to the growth of most banks. This marketplace distribution disruption didn't happen overnight, so retailers had every chance to fight back as some still are.
Why do the examples above matter to retail bank marketers? The key for me is the amount of publicity that retailers receive in terms of public sentiment along the lines of, "I love the store experience and enjoy going there (Borders), but I never buy anything from them". In retail, this phenomenon is called 'showrooming', where a customer visits a bricks and mortar establishment only to buy online later. Whether for convenience or to drive down pricing, this activity is disrupting the distribution model.
Retail Industry Parallel to Banking
Are visits to your branch as frequent as in the past? Are your customers still using checks as much as they did in the past? What about those customers that are already 100% digital and haven't visited a branch for years?
Trendsetter customer behaviors are likely to become mainstream customer behaviors at some future date similar to the trendsetting mobile banking customer or the trendsetting photo check deposit customer. When will these behaviors become mainstream? I have no idea. But people who follow the financial services industry would say it is sooner than most retail bank marketers would hope for (see recent post entitled, 'From Passbook to Mobile: The Evolution Of The Bank Account' by author and Movenbank founder Brett King).
Relying on incremental technology advancements and talking about or playing along with the latest fads, such as big data, will not put you ahead of the new competitive aggressors. We arguably already have examples of fintech start-ups big enough to enter the mainstream banking sector such as PayPal globally, Intuit in the U.S., Square in the U.S., Fidor Bank in Germany and M-Pesa in Kenya.
Even newer and smaller start-ups such as Simple, Bluebird from American Express and Walmart, GoBank from GreenDot and the soon to be introduced Movenbank should be watched for innovations and trends that can quickly move market share.
The specific challenge for retail bank marketers is to realize the potential of big data (or whatever you want to call expanded customer insight) and to stay up with, or eventually move ahead of, customers and the competition. Find ways to use the data at your disposal today more effectively and efficiently. Find ways to interact and communicate with customers in the manner they prefer in real time. Become proactive as opposed to reactive to customer needs.
The ultimate goal is to not sit on the sideline and become a dinosaur that is driven to extinction by an unforeseen player that created a new future.
About the Author:
Darren Oddie is the CEO and co-founder of AGILEci, the only business intelligence consultancy and customized software provider uniquely designed for marketers. Darren has held senior marketing positions at Visa, American Express, Glaxo SmithKline and Reuters. He has worked across all marketing disciplines for 20 years. He holds an MBA from the University of Cape Town. He also manages a customer insight blog for marketers.
Additional Insights:
Marketing & Big Data http://www.iab.net/media/file/2012-BRITE-NYAMA-Marketing-ROI-Study.pdf
Consumer Decision Journey http://www.mckinseyquarterly.com/The_consumer_decision_journey_2373
Social Voice of the Consumer http://www.wharton.upenn.edu/wcai/files/Insights_Moe_WCAI.pdf
Interesting that you mention Amazon. As publisher of The Financial Brand, I have a (very modest) Amazon Affiliates account, used only to sell some bank/branding books (http://thefinancialbrand.com/bookstore). For the last three years, they've peppered my inbox with all kinds of irrelevant offers, things they think *ALL* their Affiliates might be interested in promoting — gifts for Valentines Day, gifts for Fathers Day, all the hottest DVDs this holiday season...
ReplyDeleteNow if they looked at their data, they'd realize that all affiliates don't run the same flavor of Amazon store. Some folks, like me, sell nothing in the retail space — just B2B books. You'd think a company as technologically sophisticated as Amazon — with its widely celebrated product referral engine — could write an algorithm that effectively tailor promotions for its affiliates. You'd think this would be a reflex for a company like Amazon. But alas, they blanks all affiliates with the same B2C/retail promotions. Fail. It's spam.
Worse, they don't let affiliates opt out of these (irrelevant) promotional emails — they are required as part of "official suite of communications" affiliates agree to. If an affiliate wants to receive important account updates — like their commissions — these crummy promo emails come along with them.
So fail, fail, fail: poor use of data + no opt-out = poor user experience.
The parable, by way of anecdote, is that if companies with as much technological stature as Amazon struggle with data analytics and/or its integration into the UX, then you know it's going to be an issue for financial institutions, most of whom run limited, closed-architecture, third-party DP systems.
An interesting article. Whilst I would agree that the the use of big data to engage with a dialogue with customers is not commonplace yet, it's certainly not a mirage for some. Some banks I'm working with are beginning to use, what I would describe as, big data, to understand their customers' preferences, their spending habits and to match this up with current, real-time behaviour, to engage with them in a more frequent way. Sending location based offers, something you highlight, is one example of this. Some banks are building networks of retail partners to provide these offers for the benefit of the end customer as well as the retailer. It's a good example of a big data project: sifting through historic information looking for spending patterns, predicting what offer someone may respond to positively and then monitoring real time events to identify the time to send the offer, and doing this for hundreds of thousands or millions of customers concurrently.
ReplyDeleteI agree that other retail driven organisations are setting the standard when it comes to this type of engagement and banks are being, in general, slow to respond. Unless retail banks really do want to end up as simple low margin utilities this is going to have to change.
I would be interested in your view on which organisations today are actually in "omni-channel dialogue with their customers to self-individualize their chosen offerings". There is not an organisation today that would not want to achieve this but if this is the expected outcome of utitlising Big Data then I would assume that all industries, including online retail are in the same boat and are running too slow.
ReplyDeleteI think companies like Amazon are getting much better at it, while they don't leverage all channels. I think there are many financials that are doing better with omni-channel communication, but have not crossed the threshold on the proactive offering side. Sitting on the sideline is not an option, however. Banks need to move toward integrating channels and consolidating silos forst and then look outside their firewalls for the rich data beyond. Start small before boiling the ocean.
ReplyDeleteThanks for the comments - always appreciated.
ReplyDeleteMy overall desire is to take away the big data hype and let's understand how marketing are using data, analytics and insight to move the retail banking game to a new level.
Examples of products that use data and individualization are Amazon (the standard consumer version that highlights similar products you may be interested in and you can further tweak to ensure it's relevant - very different to what a physical book store can offer you), iTunes which does the same for music and video, Tesco supermarket in the UK profiles you and you can add 'data' to it to make communications and offers more relevant. These companies are not perfect, but at least we're seeing how digital and use of data can change the product offering. I've thrown Tesco in there as they are a large company and have embraced multiple channels, so it's not impossible for companies to adapt.
It's not just about the communication, it's tailoring the product. Bespoke or individualized products used to be the preserve of the very wealthy and are now accessible at the value end of product ranges (e.g. automobiles).
Omni-channel engagement changes the game. Many people now view mobile and tablets as integral to their life. We don't expect to visit a bank branch, we don't want statement inserts (we don't receive paper), we don't want offers not relevant to our lifestyle or purchase habits, we don't want to be told how to interact with our bank and we expect transparent interactions. We've had years to attune our senses to lousy marketing and we treat it with the contempt it deserves (Jeffry - it sounds like Amazon are lousy at some marketing).
My overall point is if retail banks are using big data in marketing to move the game on for retail customers then please shout about it. Don't jump on the bandwagon and call your analytics big data if it's just a bigger version (i.e. no more sophisticated) of what you've been doing for years...please!
In have had a brief experience with a marketing department in big Dutch bank. There focus was only on database marketing and it seemed very narrow minded to me. In my experience it is very hard to make the 'right offer at the right moment'. If you look at Amazon, Netflix, Apple or any other online retailer they know what I am buying, but there suggestions are always more of the same genre. It never seems very deep or knowledgeable. Only last.fm is a great example and really let me discover new music. But the point I want to make is that there classic marketing tools still work. The brand and the story it tells is still important. My experience I had with bank marketing can be found here. I am curious about your opinion about database marketing vs brand building.
ReplyDeletehttp://www.brainbulb.nl/bank-marketing-reviewed/
Darren, enjoyed reading the article and found that your conclusions are in line with eh P2C 5th Annual Digital IQ Survey which shows that while 62% of executives believe that big data has significant potential to create business advantage, 58% indicate that transitioning from data to insight is a major challenge. The study goes on to show how 41% note that their systems cannot process large volumes of data from different sources.
ReplyDeleteThis coupled with their retail banking trends study with 62% of consumers shifting to the internet as a preferred channel of interaction, reinforces the urgency with which banks need to jump on the data analytics, omni-channel delivery band wagon.
Thanks for reinforcing these points in an article which I'll be sharing with all of bank marketing colleagues.