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Bank of Scotland
Bank of Scotland Improves Customer Service with MicroStrategy Software
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With increased pressure from new competitors, such as supermarkets and energy suppliers entering the financial services market, Bank of Scotland needed to ensure the loyalty of its existing customers while attracting new ones. |
The bank decided to restructure use of its data warehouse in order to focus its marketing strategies more successfully and better understand customer lifestyle patterns and behaviour. So far more accurate data analysis has led to increasingly successful marketing campaigns. Customer response and take-up of promotions has tripled, with more than 10% cost savings on direct marketing and advertising resources.
Unlocking data to improve product marketing strategies through precise targeting and more effective advertising, was one of the prime aims of Bank of Scotland when it undertook a data warehousing sales and marketing pilot using tools from MicroStrategy.
The Bank of Scotland Group, which includes Bank of Western Australia, Capital Bank, Bank of Wales and British Linen Bank has enjoyed steady growth over the last few years. Last years tax-free profits were a record £779.1 million, an increase of 14% over the previous year. The operating profit of the bank at £45,750 per employee is one of the highest in their peer group, and at 50%, its cost income ratio is one of the lowest. Internationally there are offices in London, New York, Chicago, Boston, Houston, Jacksonville, Los Angeles, Hong Kong, Moscow, Paris, Frankfurt and Seattle.
Bank of Scotland was founded over 300 years ago as a retail bank and still retains 325 branches focused on personal and business banking services, with the emphasis on quality of customer service and local decision making.
Bank of Scotland has 95% of its branches in Scotland and corporate offices throughout England. In order to provide a wider range of distribution channels the bank launched its direct banking arm in 1980. It also provides the banking services for Sainsbury's Bank a joint venture project between J.S. Sainsbury and Bank of Scotland. This mutually beneficial move gives the Bank of Scotland a greater presence in England while Sainsbury's benefits from Bank of Scotland's banking expertise.
Market research shows that Bank of Scotland already enjoys high levels of customer satisfaction. In surveys, it is consistently rated higher than its main competitors. Bank of Scotland wants to ensure it maintains its excellent customer relations and this places a new emphasis on effective use of targeted direct mail as an aid to communication and the relationship building process. Karen Inglis, Head of Strategic Analysis explains "We have given customers so many ways of contacting us - via the branch, telephone, HOBS (Home and Office Banking Service) and email. This is a measure of the commitment of the bank to use the latest means of reaching customers.
This comes at a time when new competition is joining the banking arena in the UK. Building societies are converting to banks, while supermarkets and other retailers are providing financial services, and utilities such as Scottish Power and British Gas are also entering the market. "If we cannot show our customers that we understand them, that we value them and can serve them better than these new competitors, we are at risk of losing them" explains Inglis.
The starting point for the project was the data quality and analysis. Inglis admits "The quality of the existing data could have been better. The database was also scattered and unstructured with several hundred different product codes. We didn't have an analysis tool at that time so we didn't bother to even try to analyse. The dream was to provide a single database that everybody could work from."
"Just starting this initiative has positively increased savings, but without the underlying understanding of the market there is no way of knowing how good this really is against current market conditions. If the potential for increase in the market is 50% then a 10% increase is not a significant number. The aim of the department is to provide and understand all of the necessary figures required to do the marketing and planning for increasing business and productivity," says Inglis. The response to this was to start work on four development strands focused on data quality, the development of a marketing information system together with the establishment of new direct marketing processes and procedures, and the research and analysis necessary in order to identify and set suitable benchmarks.
The data quality was audited to establish exactly what the problems were with the existing data sets - were they in poor shape? How critical was the data? And most importantly, which parts of the data sets were of most use? The decision also had to be made about where responsibility for the data lay - with the branch, centrally or both?
A central clean-up was started and the systems used changed, when it was discovered that the use of mandatory fields in order to improve data quality was, in fact, having the opposite effect. Measures were taken to address the internal data entry issues. This improved the content and accuracy of the existing database, but added no additional information.
A data quality programme based in the branches was then set up to ensure the improvement in quality continued for existing and new data. The focus was on raising the awareness of the project by education and communication. Inglis says "We used workshops, seminars and bulletins to tell people why data was important, and what use could be made of it. Training in data awareness is now part of our core competencies for all staff and makes a huge difference to data quality".
Of the marketing information system, Inglis says, "When SAU was founded we started to develop a marketing information system, to improve the analytical component of what we were doing. But things have moved on and we now have a marketing information system consisting of three parts - market analysis and planning, operational marketing including the campaigns and operational research, which is our statistical analysis, modelling and data mining functions". Inglis continues, "This was a difficult model to build as it had to be based on the information our managers needed, not the information they were used to receiving. Eventually, the data requirements fell into seven separate dimensions, customer, transaction, geography, time, contact history, channel and product. This was the starting point - what our users then wanted to do was to use any dimension in any way and with any combination of the other dimensions. The functional requirements of the system was that it had to be easy to use with up, down, sideways, anyway drill functions and use intelligent agents. Technically it had to integrate with our existing systems and be easy to manage."
With this preliminary specification, the bank identified potential vendors producing a short list of four. MicroStrategy Agent was chosen as the preferred solution, explains Inglis "We prototyped the four selected offerings, but MicroStrategy Agent was clearly the one that fitted into our model, exceeding all our functional and technical requirements. We now have the specific data we need for key marketing processes. MicroStrategy Agent is an excellent analytical tool; we can do selections in a number of different ways including customer profiling, customer segmentation and even event-driven marketing. So if a customer moves house, a few months later we can contact them regarding household insurance.
This has given us the edge in designing much better integrated marketing campaigns." To complete the picture another couple of tools were added for more sophisticated statistical analysis and data modelling.
The business case for undertaking this initiative is compelling. Improved marketing has already saved 10% of the direct costs by more precise targeting. The advertising budget has also made 10% savings through instant response monitoring and pulling non-effective advertisements, and re-investing the budget into the more effective campaigns. Cross sales have improved, and the contribution per product has increased, as well as the product penetration per customer. "We did the sums on this, and took the most pessimistic view we could. Even assuming a product life of only five years, and less than 2.5% efficiency at cross selling in year one, the answers still came out to tens of millions! But, we still had to lobby hard for the project and take the decision makers through all the numbers before they were finally convinced", states Inglis. In reality the results are better than predicted. From a 1% response to a particular promotion with a 0.8% take-up in 1996, the bank has tripled this to a 3% response and 2.5% take-up. Further analysis has shown that by clustering into life stages the take-up is as high as 12% - useful information for planning a clearly targeted campaign.
When asked about the lessons learnt from the project Inglis replied "I can't emphasise enough the issues of data quality - it is critical to everything we do. There is no point in having sophisticated models using bad data - you can't profile, score or target without good underlying data sets. We now have a team of twelve just working on data quality and particularly concentrating on our customer information file. We also discovered the benefits of prototyping, especially important in getting the users involved in the project so that they feel comfortable with the techniques and experience the benefits first hand. Finally, phase the development - don't do everything at once. Use a small data set and provide fast visible benefits that justify the whole process."
The sales and marketing pilot and the use of sophisticated decision support tools has tripled the response rate to focused marketing campaigns and demonstrated the power and potential of using these tools. The next step was that the SAU has become a centralised unit serving all the divisions of the bank, not just the retail banking division, and the tools, techniques and expertise acquired in the pilot stages will be extended to all the other business areas as a full corporate data warehouse is built. MicroStrategy products and tools will continue to be deployed, as the customer management approach is phased into more business units and divisions.
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With increased pressure from new competitors, such as supermarkets and energy suppliers entering the financial services market, Bank of Scotland needed to ensure the loyalty of its existing customers while attracting new ones. |
|
|
|
|
| |
The bank decided to restructure use of its data warehouse in order to focus its marketing strategies more successfully and better understand customer lifestyle patterns and behaviour. |
|
|
|
|
| |
So far more accurate data analysis has led to increasingly successful marketing campaigns. Customer response and take-up of promotions has tripled, with more than 10% cost savings on direct marketing and advertising resources. |
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