CMOs lead the data revolution
Data is an information asset that leads to deeper insights into your markets and customers. In the age of Big Data, the combination of unstructured and structured data has multiplied the value of information. The use of that data will boost the growth of business, remove inefficiencies, and meet customers’ needs and expectations, while gaining a competitive advantage. But to extract the maximum value from your big data riches, you will need a plan.
CMOs take the lead with analytics
The chief marketing officer (CMO) stands out as the single largest successful user of data, well ahead of nearly all other executive roles, according to a new study—The Data Directive—commissioned by Wipro and conducted by the Economist Intelligence Unit. About 50 percent of CMOs polled in the survey have seen a clear, positive difference in using data to improve their understanding and segmentation of customers. And 40 percent of CMOs surveyed saw similar merit in using data to increase sales.
In the report, Philip Clement, global chief marketing officer at AON, called the scope of how data can improve marketing “absolutely huge.” Earlier in his career, Clement used analytics to try to identify the typical characteristics of consumers who might, say, be interested in muscle cars. “Now, it’s just the opposite. You literally know who the person is that likes muscle cars,” he said.
Customer analytics is not new, but with the emergence of predictive analytics and big data, companies are finding new ways to deepen customer engagement and hone their marketing. With data analytics, organizations can make predictions in otherwise unpredictable markets and with unpredictable consumers.
According to the Economist Intelligence Unit study, CMOs believe that increasing cross-selling efforts and optimizing the marketing mix are the top areas in which data has the greatest potential to deliver results.
“Event contextual offers, or the next-best offer, will help create true differentiation, as opposed to a traditional predefined, campaign-based consumer approach or a mass marketing-led consumer approach,” says Nitesh Jain, general manager and global head of the Advanced Analytics Practice, Wipro Technologies.
Get a 720 degree view of customers
Organizations go to great lengths to understand their customers better from a business perspective. Big data analytics can be used to provide a more complete picture of your customers from both a business and a personal point of view, and this level of visibility helps to better predict purchase habits. This insight enables you to meet your customers’ needs and expectations more precisely, which leads to greater satisfaction, stronger loyalty and increased sales.
One of the most effective ways to apply analytics and uncover business opportunities is the 720-degree business view. As its name suggests, a 720-degree review goes well beyond the traditional 360-degree view. Applying a 720-degree view to customers helps you understand how they use products, which in turn helps you to discover new opportunities to sell add-on products or services, or develop new products or services.
Customer data sources and perspectives include:
• Internal: Your view of the customer through your own sales data
• External: Other companies’ views, which may be available through third parties
• Transactional: Credit card company or bank view via transactions
• Digital persona: Social media exposure, blogs, search data.
Analysis of the different views of your customers is the basis of a more accurate model for predictive analysis and decision making.
A roadmap for analytics
One of the ways would be to start the journey to analytics with a 90-day plan. Begin with an honest assessment of your organization’s IT abilities, what your company wants to accomplish with analytics, and how to make changes to get there. Next, identify the tools and skills required to turn your raw data into useful information. Identify IT changes that are needed up front so that you can filter the data according to your needs and define the migration paths needed for clean and valuable data.
For almost any business, there are four phases to customer analytics processing and adoption:
• Customer prospecting: Using analytics to identify new markets to enter, new products to develop, and new customers who want what you’re selling.
• Customer acquisition: Acquiring and applying data to enter new markets, and to attract and persuade new customers to buy your products or services.
• Maturing relationships: Mine your existing customers to identify new opportunities with them.
• Continuously measure: The goal is to never lose a customer relationship, and never miss opportunities to grow existing relationships and form news ones.
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