Picture this scenario: The CMO is meeting with his boss, the CEO. At the top of the agenda is discussion of marketing effectiveness and ability to drive predictable revenue. In other words, the CEO wants the marketing chief to quantify benefits to the company. If this CMO is like many, however, that question will not be easy to answer. In a 2011 IBM study, for example, 63 percent of CMOs said that return on marketing investment (ROMI) would be the most important measure of success by 2015. But only 44 percent reported feeling fully prepared to account for it.
Customers engage brands across traditional, online, social and mobile channels in complex relationships that defy conventional measurement. To drive improved ROMI and predictable revenue, marketing needs to know how, why and where consumers buy.
That’s no simple job. Where does mobile app engagement, for example, fit in the broader customer journey? How does web engagement translate into offline sales? What’s the predicted lifetime value of a satisfied buyer? What the marketing team needs is actionable insight from the trail of data that customers leave behind. Yet common practices stand in the way:
- What’s Wrong With Marketing Silos?
Consumers don’t restrict themselves to shopping in one channel. In its Holiday Shopping Intentions 2012 study, Google and Ipsos OTX found that 51 percent of respondents reported they would research online and then purchase in-store, while 32 percent said they plan to research online, visit a store to view a product, then return online to purchase. And 17 percent said they would view in-store and buy online. Measuring performance within individual channels, as marketing often does, leads to misinterpreting who buys and how.
- Why Don’t Top-Line Metrics Work?
While key performance indicators (KPIs) are helpful in aggregating data, they can be interpreted in an infinite number of ways. Top-line measures like page views or conversion rates are almost never actionable. Customer satisfaction metrics, for example, show you whether your customers are “happy” at a given time. But the metrics will not reveal what causes churn or drives repeat sales.
- What’s Wrong With Current-State Metrics?
Current-state metrics are like thermometers; the are capable of telling you the temperature but provide no meaningful intelligence about the future. If all you plan to measure is current temperature, you can simply open the window. You need to go beyond “current state” to predict – and impact – future states.
Customer Insight From Digital Analytics
Digital analytics give marketers the power to overcome these challenges by integrating and analyzing data across all marketing channels and customer touchpoints. Here are the three steps required:
- Segment Customers.
Marketers have been doing customer segmentation for years. But today’s multichannel marketing requires a multi-tiered approach. Every metric needs to be seen in the context of “who” is engaging, “where” and “why.” You can model, for example, mobile touchpoints, social media buzz, web visits, call-center calls, ATM visits, in-store visits and more with a simple model of customer type, recency and frequency of engagement, and success. Data then becomes the foundation for audience microsegmentation, the key to dramatic campaign improvements. Rather than targeting consumers as large groups (e.g., men of a certain income), you reach individuals in personalized ways based on preferences in search and engagement patterns, demographics, and even social and interest graphs, along with campaign responses.
- Integrate the Silos.
Marketers also need to know the direct and indirect interrelations between these data points to determine what leads to a purchase. But almost every digital source has vastly different characteristics and may be interrelated in indirect ways. Effective integration requires analytics insights at buyer microsegment levels. In a 2012 Social Media and the Holiday Shopper survey by Clever Girls Collective, more than 93 percent of women shoppers said they would buy based on trusted bloggers. And nearly the same number said they would purchase if a brand shared coupons, deals, tips or ideas via social media. Data integration using digital analytics combines data streams at visitor and campaign engagement levels, with data overlays for such elements as seasonality, demographics, social patterns and geo-location.
- Discover the Levers of Change.
Finally, your analytics should provide insight into how to create the future you want, not just measure the current-state. That means performance reports must correlate variables and changes in how consumers respond to your marketing campaigns. Let’s say you want to understand how social buzz influences paid marketing campaigns. You can overlay data from social analytics solutions with your paid campaign data across each channel to identify interrelationships and correlate how social buzz has affected results.
A Case Study
Let’s look at how the U-T San Diego, a top 25 daily news outlet, uses digital analytics to engage readers and drive advertising revenue. The publisher began with a clear goal – increase revenues and each author’s traffic by 15 percent year-over-year. This was an exceptional challenge following this publisher’s June 2011 transition to a paid-content model online, which has been shown to decrease readership by more than 40 percent at a typical news organization.
Digital analytics give marketers the power to overcome these challenges by integrating and analyzing data across all marketing channels and customer touchpoints.
Using digital analytics, the U-T can connect to and analyze multiple data sources in real time in order to identify how reporters and photographers can increase content monetization — both on the site and through referrals from their social-media accounts like Facebook, Twitter, and Pinterest. Which headlines drive social traffic? How much does social engagement impact readership of each author?
These multichannel insights provide content creators and advertisers a much clearer picture of both content and ad performance, in some cases enabling individual authors to increase their readership by as much as 400 percent. At year-end 2012, content authors’ article visits increased more than 20 percent over 2011.
Digital analytics enable you to go beyond simply “taking the temperature” of the marketplace after the fact, instead generating deep insights into complex buyer behaviors and giving marketers the ability to uncover new sources of revenue.