Nice Knowing You
- Article 1 of 6
- Database Marketing, March 2002
Robert Buckley outlines the challenges that face Web marketers in identifying and tracking customers and the current methods used to keep them in sight.
One of the big appeals for marketers of the web is the possibility of cheaply and quickly developing one-to-one relationships with potential customers. Companies can develop web sites that are personalised for the individual and his or her interests and can easily acquire lifestyle and demographic data for targeted campaigns. But how much can a company find out about users and their behaviour? And, more importantly, given the number one concern of web browsers is privacy and security, how much should they try to find out?
“In the traditional world, data is expensive and time consuming,” argues Paul Mitcheson of analytics-tools company SAS. “You incur a certain amount of cost dealing with it. But online, you can record whatever a person does in terms of requests or interactions.” Every web server can log which pages, images, and other files a web browser has requested, as well as details about the web browser itself, at a cost as little as the price of storage.
But online analysis has its own data cleansing issues. There are problems that you will need to overcome to establish that one request comes from the same person as another request.
“One of the most difficult challenges is unique visitor identification,” explains Ian Thomas, strategic development director for WebAbacus, a start-up that develops a web-log analysis package of the same name. “One technique that InterShop (among others) uses is a session ID,” explains Thomas. By generating a long string of numbers for each browser and adding it to all the links on the pages sent to it, all requests are uniquely identified in the web log. By studying the order of requests that contain the identifier, you can analyse the browser’s “clickstream” – the path taken through the site by the browser.
But, if customers leave the site or close their browsers, when they return to the home page, the web site will no longer recognise who they are. And if they have not registered at the site and are anonymous browsers, you will not be able to track their behaviour over time, only within that access or “session”. Even registered customers will not be recognised until they have logged in again. Its main advantage, however, is when it is used in combination with email campaigns: by creating these personalised links for each email, you can identify which links of which emails are being clicked upon to take them to your site. You can also set up HTML emails to access your servers for similarly marked up images, showing who has read the emails, even if they never click through to your site.
By far the best method of identifying returning visitors and of tracking them between pages is a cookie – a small file placed on the customer’s hard drive by the web server, which contains a unique identifier. If the web server has extended logging turned on, then it can record this identifier with every request listed in the log and the cookie will remain between sessions so that it can identify returning visitors.
Another advantage of cookies, according to Rufus Evison, CTO of tracking-package developer Clickstream, is that you can still track behaviour by the customer that does not involve interactions with the server. “We can do things with cookies that surprise people. You can trace people offline, tell if someone is looking at a page, and see if they’ve gone away and come back. You can even do that with cached pages.” Clickstream’s software embeds a JavaScript in web pages that stores measurement data such as page display times in cookies, even if the browser is caching the page on the hard drive to speed up access. When the user connects back to the server, the server reads the measurement data in the cookie.
Web logs, together with JavaScript, can also give information about the time zone, the ISP that provided the Internet connection used by the visitor, the referring page which linked to the site and the time of day at which the visitor arrived. John Woods, CEO of Site Intelligence, says that his company’s studies of consumers’ ISPs have revealed interesting differences between ISPs’ customers. “A Freeserve user is twice as likely as an AOL user to buy something online,” he claims. Site Intelligence’s products analyse the behaviour patterns of web site visitors, and Woods says the time of day that a customer arrives at a site can be significant. “During the working day, you’ll get a lot of visitors who are sat at work, browsing sites for product information. They’ll probably be in a hurry because they don’t want to be caught by the boss while working. And they’ll have good jobs because they have internet access. Those browsing in the evenings and the weekend are a more general group. So you can customise your home page to make it give as much information as possible during the day, and alter it for the evenings and weekends.”
You can also use the referring site for demographic analysis. SAS’s Mitcheson says the most common determinant used in lifestyle and behaviour analysis is the referring site. WebAbacus’ Thomas gives an example. “One organisation we worked with runs a recruitment site. They discovered the kinds of jobs people were looking for were very closely related to the search engine they came from by quite a wide margin: 80-20. Those looking for IT jobs came from Google while those looking for secretarial jobs came from Ask Jeeves for instance.” However, Thomas cautions against some of the claims made by various log analysis companies. “Some say you can narrow down which city the visitor comes from. What you end up discovering is there’s apparently a lot of people in Leeds – but, actually, that’s where Freeserve’s based. A lot of log file analysis is intrinsically inaccurate and you have to work round it to get meaningful and defensible conclusions.”
The goal of most analysis is to tie in the data obtained from the online world with that from the offline. “The thing we became aware of over two and a half years was there are two factors in ecommerce: what marketers want to do and what consumers want,” believes Amanda Chandler, director of data protection for Internet advertising company DoubleClick. “Marketers think it’s a fantastic idea to link them, but individuals think the marketers know too much about them.”
And DoubleClick should know. The company ran in trouble in 1998 when it merged with Abacus, a company that maintained information about customers of catalogue companies, and has just dropped a consumer tracking service from its US portfolio of services. “The media and privacy advocates just saw the merger, put two and two together and made five. They assumed that companies with two large datasets would merge those datasets and build up profiles of people and what they did online.” Because DoubleClick adverts appear on many sites yet come from its own servers, the company has been able to build up a database of sites that visitors have been to using the unique identifier in its cookies. It has 100 million anonymous profiles of browsers’ personal interests for tailored advertising - the service it has dropped because of the slowdown in online advertising, it claims. But, says Chandler, “to link to Abacus’ database, the databases needed to have something in common. And there was nothing common to the cookie clickstream data and the Abacus database.”
Without some way to match clickstream data to offline data, it is impossible to combine the two. Name and postcode from web site registration information can be used as the key fields for linking the two. Loyalty card numbers are another way for the card provider to link offline and online purchase histories. Using credit card data would breach contracts with credit card companies, however, so before combining any on- and offline datasets, “take good legal advice and make sure you don’t do anything that would shock the average customer”, says Woods.
Nick Bidmead, CEO of NCorp, whose Ijen technology profiles users via clickstream analysis, says that “a privacy statement on customer-facing propositions” helps people understand what is being done with data collected on the site. DoubleClick requires those who use its ads to have links in their privacy policies to its own policy for the same reason.
Woods points out that a web site is doing well to convert 3-4% of its visitors into buyers or to register, so that means 95-99% are anonymous visitors. Behavioural analysis avoids privacy concerns, is more productive than attempting to tie in with offline lifestyle datasets and “many people enjoy the anonymous surfing experience”. Both his and Bidmead’s technology observe the interactions with the site made by visitors using clickstream and search engine analysis. The Auto Trader site uses Ijen to understand what is important to individual customers using the searches the customers make and the results that interest them. “It might find people are price sensitive or they prefer prestige German cars, for instance.”
Mitcheson agrees. “You can pretty much do all the personalisation by group without knowing the identity of the individual and flying into data protection implications. And if you keep all the data, you’ll run in data storage issues which are horrendous. The vast majority of profiling isn’t one-to-one marketing: it’s done as quite tight segmenting, targeting groups of 10-20 or 100-500 rather than a million. The biggest uplift comes from getting the web infrastructure sorted by identifying how it’s being used, the sweet spots and which marketing campaigns are drawing in visitors. You can get average spend up by another 60%.”
“The difference between web sites and department stores,” says Thomas, “is that you can break up a web site and segment it in many more different ways than a department store.” Online customer analysis makes use of different techniques to its offline counterpart, but produces similar results. While traditional marketers may want to use postcode-based lifestyle data and other tools of the offline world for segmenting their online datasets, the greater numbers of interactions and tracking techniques, together with the anonymity of the web mean that behavioural profiling produces far better results without the privacy concerns.
Case Study: Motorola and Ogilvy Interactive
Motorola planned to run an online advertising campaign last year for various mobile phone handsets and wanted to be able to track how customers responded to the ads and to its e-commerce site. Ogilvy Interactive, which designed the campaign, used WebAbacus to track visitor behaviour.
“There was a different creative execution per model,” says Janet Winslade, project manager at Ogilvy Interactive. “WebAbacus tagged up the whole batch of sites created for the campaign and for each visitor, we were able to take the referring source, which creative they’d clicked on, the position on the site, and whether they’d gone through to purchase anything. We were able to give Motorola a picture of how they used the site.”
Motorola’s existing customer database was segmented by behavioural types and the company segmented the clickstream analysis by customer type. The company compared how it expected visitors to behave, based on its existing segmentation, with how the visitors actually behaved, using the visitors who went on to make purchases through the site to match datasets. “What they found was some really strong correlations between the expected user behaviour and the behaviour they found. But in selecting sites for the creatives, while there were some good matches, some weren’t.” The company was able to determine which creatives on which sites were bringing traffic to its own sites and adjust accordingly, reducing the distance from entry to the site to purchase at the same time.
In addition, Motorola now has a better idea of which sites are the best with which to partner for its developing affiliate campaign. “We could demonstrate the ROI all the way through,” says Winslade. “And from the point of view of advertising, the numbers were very good, quite encouraging. Although you hear a lot about how no-one clicks on banner ads, a good proportion do.”