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Analytics | Business Intelligence | Management Blog by dmcnab

Dave McNab is a Sr. Managing Consultant with IBM Business Analytics and Optimization Strategy practice in Toronto. Dave has 25+ years experience in industry & consulting. He invented the patented "FlowTracker" customer behaviour analysis method for banks. See:
Customer behaviour analytics - http://www.flowtrackeranalytics.com
Customer value management - http://www.objectivebusiness.com

Posts: 17 | Created on May 15, 2009 | 4

Customer Analytics Evolution: what can we learn from the rear-view mirror? PART III

By dmcnab in Analytics | Business Intelligence | Management on Monday, January 30, 2012 11:11 AM 1
Tags: abc costing alm analytics basel accords cif customer information ftp history insights leadership liquidity management research risk management stress tests technology transfer pricing | Post a Comment

 

Understanding the motives that drive customer behaviour is increasingly being recognized as essential to relevant customer interaction. Knowing that customers are likely to drop a product or add a new one, or detecting abnormal changes in account use provides only a small part of the information you need to have a meaningful conversation with your customer. Historically our capabilities have addressed identifying what customers are likely to do (see article parts I and II) with little regard to why.

 Leading banks are now exploring how to better understand motive by gathering information about what is going on in their customer’s lives, and developing offers and dialogues that are relevant to the individual in the context of their changing circumstances. Detecting “life events” such as birth of a child, cohabitation, going to college, buying a home, renovating, acquiring a vacation property and the like is not easy.

Some of this information must necessarily be solicited directly from your customers, through interviews or online tools that provide the customer with more relevant advice when they share details of their circumstances with the bank. These capabilities have long been used in the investments domain to gather a fuller understanding of customer aspirations and needs, while satisfying “know your client” (KYC) regulatory requirements. There are now many financial planning and customer dialogue scripting tools available to engage your customer and extract vital insights into circumstances and aspirations that can be used to tailor offers and interactions to be more relevant to the individual person you are serving.

 Implementation of similar life event dialogue tools is now growing in popularity among leading retail banks. Asking your customers about their life events must involve a meaningful exchange of value to work. Customers must perceive a real benefit to providing information about their plans, aspirations and circumstances, and perhaps more importantly, if they proffer this information they need to see that your bank remembers it, protects it and utilizes it intelligently to improve the relevance of customer dialogue, offers and interventions. Failure to use information you ask for is worse than not asking in the first place. A coordinated customer dialogue requires integration across products, geographies and distribution channels with a consolidated understanding of your customer as the common base.

 In addition to revealed motives gleaned from customer dialogue, important insights about how customers use your products and services can be gleaned from traditional information sources. The big challenge is getting past account or transaction based analysis to understand holistically what your customer is doing. Traditional banking systems fragment customer behaviour into sets of transactions that obscure what is really going on. For example when a customer borrows against their home to invest in mutual funds, banks see the two sides of the transaction as unrelated (and even contradictory) events; borrowing and investing. It is only when both sides of the event are seen together that we understand the customer’s real behaviour.

 Taking a holistic view of customer use of products and services enables you to gain insight into customer intent. 30% of account level growth and diminishment occurs because your customer is switching money from one product or service to another. Transaction and account analyses fail to see these important flows of funds – everything is seen as a win or a loss of business. This distortion leads to false targeting, false triggers and irrelevant customer dialogue (see blog entires What is a cross-sale? and Event detection). Let’s take a look at how customers move money around inside the bank:

Customer moves money between    Possible motive

Accounts of the same product            Features, location

Deposit or lending products               Rate, features, location

Deposit and lending products            Borrow to invest / pay down loans


In addition to moving money between existing accounts, your customer may be moving into a new account or product at the same or a different branch. These changes, normally observed as sales and lost business, indicate clear product or location choices that are conscious choices your customer is making to reallocate their money within your bank’s products and services, and you need to understand why. For example relocating accounts may be indicative of a change in job or residence – a major life event. Paying down loans suggests that your customer has recently acquired new wealth. Borrowing to invest may imply an impending major purchase.

You can refine these insights by knowing which products are involved. For instance borrowing from a HELOC to invest in short term mutual funds may indicate an impending renovation, whereas borrowing from a HELOC to invest in equities or long term CDs likely indicates a change in investment strategy. Knowing what your customer is doing holistically reveals – at least partially – their intent, which should inform your customer dialogue.

Switches between deposit and lending products are another interesting case. These substitutions – often called cannibalization – illuminate customer preferences. Within deposits, for example a customer can move money between products with different liquidity characteristics (short term, long term, demand) and with different rates of return and risk. Changes in preferences reflect changing customer needs which you should be aware of.

Analysis of this type reveals a lot about customer behaviour. When you combine this data with other information acquired through tools designed to gather life event data you can sharpen the relevance of your dialogue significantly. Moving beyond the analysis of individuals, statistical techniques can be applied to your entire portfolio of customers to better understand, predict and optimize your customer interactions by first understanding why customers do what they do.

- Dave McNab


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