How Confused.com found clarity in customer data

A greater understanding of the customer means smarter targeting

The leading UK price comparison website Confused.com has deployed SAS® analytics to better understand and segment millions of customer contacts, to provide new insights to enable additional marketing channels, optimize campaigns and work towards providing online product referrals

UK insurance provider Admiral Group launched in 1993 with one brand, 57 employees and no customers. Today, the business has nine successful brands including elephant.co.uk, Bell, Diamond and Gladiator, over 1.75 million customers insured and more than 3,000 staff worldwide. With annual group turnover around £900 million, the business also owns Confused.com, launched in 2002 as the first insurance aggregator website. Confused is designed as a one-stop shop for automated online price comparisons, helping consumers find the right deal in car, home and travel insurance as well as utilities, personal finance products like credit cards, and more. To support Confused.com's continued growth — to help it understand customers and make customer contacts more relevant and so more profitable — the company has implemented SAS analytics.

SAS gives us a much better idea of who we should be targeting … I can certainly see us improving customer retention significantly and improving the relevance of campaigns. And there's also a lot of potential to improve onsite processes and help inform new product development, so there are wider impacts for the business.

Nerys Chaplin
Analytics and BI Manager

Increased competition and higher acquisition costs

According to Nerys Chaplin, Analytics and BI Manager at Confused.com, a major driver for change was increased competition amongst aggregator and price comparison websites, with higher acquisition costs resulting from extensive TV advertising. And the business opportunity continues to grow, with the recession meaning consumers want to 'shop around' even more, further increasing traffic to the site.

"Our main requirements for SAS were to reduce our cost of offer, bring down marketing costs, improve cross-sales with other products on the site, and improve retention marketing," says Chaplin. "We wanted to improve the level of customer insight available. We are also developing a lot of personal finance products that require an improved level of one-to-one targeting."

Confused.com is responsible for high levels of media expenditure, an investment leading to a large data store that includes Europe's largest motor insurance quotation customer database; data is held in SQL Server. A logical next step was to ensure the company had the people, processes and technology to transform this data into actionable insight.

"Previously, customer insight was limited to information gathered from the car insurance quotation process, with no segmentation apart from very simple demographics like age and TV region," Chaplin says. The business used email as virtually its sole customer contact marketing channel, delivered via a third party provider. The opportunity was to become far smarter in targeting to improve uptake and response rates. Indeed, Confused.com already had millions customer contacts, with a high proportion including active email addresses; this potentially valuable resource was waiting to be exploited by the right analytics.

Why SAS?

Confused.com considered a number of options including SPSS before choosing SAS based on its proven analytical capabilities. "I'd worked with SAS before and was sure it provided what we needed," says Chaplin. "On the analytics side I knew we'd be able to do things like propensity models and segmentations, and have the ability to crunch through large data volumes and bring disparate sources together."

SAS delivers a versatile toolset for users to access data from anywhere and then transform it into usable insights. Data sources at Confused.com include the SQL-based main customer data warehouse, which gathers data from all the website interactions, and data from the third party email services provider. The business plans to add more sources including external data from information provider Acxiom, and also tying web analytics tools into SAS.

Revealing who buys what, why and when

Chaplin describes the company's use of SAS as a "server-based solution that interfaces with our data warehouse to provide data on all customers – we update it every week – and then carries out propensity modeling on who buys what, why they buy it, when they buy, and who are the best customers to target with different products like home insurance, utility services and, most importantly right now, financial services products." Initially, the company will focus on two types of segmentation: customer lifestyle and customer life stage. Results from analyses are already used, for example, to locate variables, enhance selections and improve targeting in email campaigns. Chaplin provides an example: "In our home insurance campaign, we use SAS to highlight the best customers based on a number of predictive variables. We can probably get 70 percent of applications through, say, 20 percent of the email campaign, which is key for us in terms of data collection and reducing how many emails we send out, making sure it's relevant. We do a similar thing with credit cards, using SAS to target fewer people to achieve more uplift."

Improved targeting, new media

Chaplin continues, "SAS gives us a far better idea of who we should target. Before, the home insurance campaign was fairly basic and used just a couple of variables." A direct feed is planned, with SAS used to support the data selections that drive the email campaigns. The analytics now available will also feed into contact channels new to Confused.com, including direct mail and SMS, while other options being investigated include outbound calling and social networking sites. "It's early days but I believe how we use SAS will have a significant impact on our business. I can certainly see us improving customer retention significantly and improving the relevance of campaigns. And there's a lot of potential in these analytics to improve onsite processes and help inform new product development, so there are wider impacts in addition to improved targeting and acquisition marketing.

"Compared to a single product provider, in credit cards, car insurance or elsewhere, we know certain types of customer will pick a certain type of provider. But we can offer consumers many more options, we have far more data and so have a far more comprehensive overview of the market and of customer behaviour. So there's a lot we can tap into. At Confused.com, we know we're sitting on a very interesting repository of data - and I don't think we'll ever exhaust the analytical possibilities available in terms of both customer and market behaviour."

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Challenge

Making use of valuable data in a competitive marketplace to gain new customer insights, better target campaigns and improve operational efficiency, enhance cross-selling and increase revenue

Solution

SAS® analytics including a range of models and customer segmentation

Benefits

Greater understanding of customers means smarter targeting, improved retention marketing, reduced wastage and lower campaign costs, with an opportunity to exploit new communications channels

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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