Companies can maximize their investments in Web analytics if they focus tightly on priorities, layer human intelligence on top of smart technology, and enlist senior management to lead the charge.
Bottom Line: Companies can maximize their investments in Web analytics if they focus tightly on priorities, layer human intelligence on top of smart technology, and enlist senior management to lead the charge.
Customers increasingly communicate with companies through digital channels, and marketers have hoped that tracking these interactions can provide valuable insights into consumer shopping habits and product performance. So it’s no surprise that more and more companies are utilizing Web analytics to gather data on Internet traffic — including emails, search engine activity, social media links, and engagement with display ads. Indeed, more than 60 percent of the 10 million most popular websites use Web analytics, according to a 2014 survey. (This high use rate is partly explained by the fact that some powerful tools such as Google Analytics are free.) Even so, the few studies that have looked into the impact of Web analytics have generally cast a downbeat tone, suggesting that most companies use the software in a random, nonstrategic manner.
In an ideal world, analytics would dovetail with firms’ digital marketing campaigns. The data could provide a snapshot of consumers’ response to Web-based advertising and let managers optimize online and offline outreach efforts. However, a 2013 study by Adobe found that although three out of four marketers thought measuring digital marketing efforts via Web analytics was vital for their business, only 29 percent believed their company was doing it successfully.
A new study seeks to shed some light on the benefits of Web analytics and provide companies with guidance on maximizing the value of the digital data they gather. To do so, the authors performed an in-depth case study of a manufacturing firm that has enjoyed notable benefits from its use of Web analytics. They also investigated two peer firms that have struggled in their attempts to implement a successful Web analytics program.
The authors deliberately selected the manufacturing sector because they wanted to test the power of Web analytics in a setting outside the technology sector in which companies have a relatively complex sales process and rely on face-to-face dialogue with customers who are deliberating, not making snap decisions based on Internet surfing. If companies in this industry can use Web analytics to improve their digital marketing, the authors reason, many other firms can, too.
All three firms, multinationals with annual revenues of between US$3 billion and $10 billion, employed essentially the same direct marketing tactics, including company websites, online campaigns, search engine marketing, display ads, email newsletters, and social media outreach. But the firms differed sharply in how they processed and utilized the glut of data they amassed.
For example, the two firms with disappointing returns from their investment in analytics mainly touted their ability to count how many consumers visited their website and track the traffic that resulted from specific marketing appeals. In contrast, managers at the company that reported multiple benefits from its use of analytics described a holistic effect on the efforts, evaluation, and outcomes associated with digital marketing.
“With the help of analytics, the management and sales teams have undoubtedly noticed that our digital services, website, and all our activities have a powerful impact, and the change has been radical in the last few years,” a director of digital marketing told the authors. “The budget is still bigger for offline marketing, but the digital marketing budget has multiplied. Last year, I think we more or less tripled our budget.”
A comparison of the firms’ approaches underscores several valuable lessons for using Web analytics. The most important element is focus. The successful company constructed its metrics system around a single priority: increasing sales. Although customer satisfaction and improving brand awareness were also concerns, they didn’t detract from the main purpose of using Web analytics to determine how a variety of direct marketing activities affected sales. This prioritization helped managers avoid information overload and saved them from wasting energy on ultimately distracting applications of the technology.
The successful company constructed its metrics system around a single priority: increasing sales.
But once you have the data, what do you do with it? Companies need to strike the right balance between automation and old-fashioned human endeavor. The study’s focal firm automatically collected data via Google Analytics and an online survey of consumers who visited its site. But managers decoded which digital marketing activities led to the highest number of sales leads. They also developed a Web analytics system that traced the stages along a customer’s path to purchase.
Although the company generated and stored sales leads in an online database, it also earmarked them for specific salespeople and teams, who could follow how direct marketing campaigns affected their ability to sell to targeted consumers. A customer data expert and a digital marketing campaign manager worked closely together to coordinate the analysis, looked for new ways to use analytics, and made weekly presentations to upper management about their results.
The final lesson: Senior leadership has to take an interest. When supervisors aren’t highly invested in digital marketing or Web analytics efforts, their subordinates lack the initiative or motivation to develop appropriate systems. Accordingly, managers should treat Web analytics seriously and make sure they give their teams the resources and ability to hire new talent. The Web analytics team requires an active leader who can coordinate tasks and create a culture that “fosters cooperation, information sharing, and data-based decision making,” the authors write.
Source: “The Use of Web Analytics for Digital Marketing Performance Measurement,” by Joel Järvinen and Heikki Karjaluoto (both of the University of Jyväskylä), Industrial Marketing Management, Oct. 2015, vol. 50