Theoretically, this marketing team has all the data it needs to do the job; in fact, the team has more information about both new and repeat buyers than at any time in history. Consumers leave breadcrumbs of data signaling, “I was here,” every time they browse for product information, read reviews, clicks ad banners, “like” Facebook pages or opt to take advantage of promotions. But these big opportunities for insight come with complexity in our increasingly connected world. That complexity only gets deeper when you correlate behavior among in-store, online, social and mobile channels, searching for why some consumers become loyal, repeat buyers, while others simply walk away.
Ask the right questions
Analytics empower marketers to decode the Rosetta stone of customer behavior: how, when and why they buy, as well as the best ways to retain them. But you need to start with the right questions and know your data can answer them. Consider these examples:
- What factors motivate repeat and more frequent purchases among your most valuable customers?
- What campaigns and offers drive repeated sales of multiple products, and how does buyer reaction differ for different segments?
- How does purchase-order size, recency and frequency relate to the likelihood of churn or new purchases?
- What factors support customer loyalty holistically across all touchpoints – in-store, mobile, social and online?
Transform Data “Chaos” Into Customer Insight
Many marketers secretly find the tidal wave of data available to them almost too much of a good thing. According to Forbes , 70 percent of CMOs feel they are underprepared to manage the explosion of data and “lack true insight.”
Here are four guidelines for building analytics capabilities that allow you to get to the bottom of questions like those above:
1. Connect your data
Consumers don’t restrict themselves to shopping in one channel. Measuring performance within individual channels, as marketing often does, leads to misinterpreting who buys and how. You need to connect all internal and vendor data. This can (and should) include many of the following: web analytics, online advertising, email marketing, social media, search-engine marketing, surveys, live chat, CRM, marketing automation, U.S Census and third-party market research, along with sales, revenue and margin data from your internal systems.
2. Identify the right metrics
Top-line metrics typically produce little actionable information. Customer satisfaction scores are a case in point. They show you whether your customers are “happy” at a given time. But the metric will not reveal what causes churn or drives repeat sales. Or think about this example in the social realm – you can measure Social Shares (top line), but more relevant is a Virality Index correlated to Purchases, Loyalty sign-ups and Cost-per-Loyalty sign-up. Note that the right metrics often include data from multiple sources!
3. Integrate the data
Your data analysis needs to reveal interrelationships among paid, owned and earned (POE) media. Correlations of behavior across traditional and digital media reveal factors driving campaign and channel performance trends. A video that goes viral, for example, may boost ROI in online banner ads or change buyer churn for the better. You need the power to correlate key demographic, behavioral, social and financial factors to find what motivates buyers and repeat buyers.
4. Course-correct in real time
Data is most valuable when timely. Track your teams’ marketing mix performance in real-time, identify the levers of change, and act now to ensure marketing is indeed driving lifetime customer value for your business.
To get all this done, know that help is at hand with marketing analytics that provide deep intelligence throughout the entire customer journey with your brand. While the underlying technology with advanced analytics is highly sophisticated, you should have an interface that allows ease of use day-to-day and actionable reports that can be distributed throughout your organization.
We’re sure your company has put a great deal of focus on customer retention. Please share your stories, comments and insights on the opportunities and challenges you’ve encountered along the way, including what you need most in terms of analytics capabilities.
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