Top performing companies are using data analysis to create a “database of intentions” to more accurately predict and respond in real time to customer behavior.
In fact, 90% of the top performing companies have a marketing analytics initiative in place, compared with 69% of all other firms, according to a recent survey by Aberdeen Group.
The biggest goals of these top performing companies for marketing data analytics are to increase the response rate of marketing campaigns; increase the accuracy of audience targeting; and boost revenue from cross-selling.
Additional findings include:
- Best-in-class companies are 95% more likely than all other companies to use real-time, click-stream analysis for customer segmentation and targeting
- Marketing leaders are 39% more likely than all other companies to dynamically update buyer profiles
- Top performing companies are 24% more likely than all others to customize marketing offers for specific market segments, and they’re 85% more likely to customize offers to individuals
“Thirty-nine percent of best-in-class companies indicate that marketing managers are able to use predictive analytics tools without dedicated statistical experts, compared with 26% of all other companies,” the report notes. “What’s driving this is an increasing ‘analytical mindset’ within companies, as well as a self-service approach to the tools necessary to deploy analytical models.”
Companies that are interested in bolstering their businesses with data analysis and real-time marketing results should consider Aberdeen’s recommendations. And they should start with data sources that are easily controlled or easily accessible like marketing automation, campaign management and customer relationship management systems.
“The expectations of your buyers have never been higher,” according to Aberdeen.“If you don’t provide a remarkable, personalized experience, the chances are that your competition will. Increasingly this requires the ability to aggregate interactions and behavior across myriad channels and touch points in real time in order to optimize the next interaction for just in time delivery.”
German Sacristan, Return on Marketing Investment Developer at Kodak, echoes Aberdeen’s findings, noting that data analysis in marketing is about first defining the data that’s necessary to help companies be more relevant when communicating with customers.
“It’s always easier to sell to someone you know than someone you don’t know,” he notes. “Profiling is so important that if you get it wrong, you might end up talking to the wrong person, with the wrong message, at the wrong time, and in the wrong way.”
Sacristan suggests answering several questions to effectively profile customers:
- What are their characteristics? Existing data on which customers are currently buying and what they’re doing can help define these characteristics. Companies can also study the characteristics of people not buying from them.
- What are the buying criteria of current customers?
- What channels do customers buy via?
- What are the purchase histories of current customers?
- Why would they buy from you?
“This is a process that sales reps have been using successfully for hundreds of years when visiting customers face to face: Listen to what’s important and disregard the rest, and then use just the important information to be more effective in communications towards closing the sale,” Sacristan says.
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