You’ve probably heard of the blind men who touched part of an elephant and were adamant about their interpretations. Businesses are in the same predicament without customer data integration for a panoramic viewpoint. In my interview with Swati Saxena, Customer Intelligence Manager at Hewlett-Packard, she outlined some of the benefits of integrating customer data:
- Better prediction and understanding of what drives customer loyalty.
- Identifying which products to sell to customers most profitably.
- Prioritizing customers to target with specific offers.
- Using the most effective messaging and communication channels, etc.
- Reducing waste for customers and the company, for improved customer experience management.
Better Strategies from a Holistic View
“Customer data integration is akin to the parable of six blind men who were brought to an elephant and asked to touch it and describe what it was,” she explained. “One touched the elephant’s trunk and said ‘this is a snake’; one touched the tail and said ‘this is a rope’; still another touched the ear and said ‘this is a fan’. Each viewpoint was useful from a narrow perspective, but none of them were accurate about the big picture. Similarly, when data is used in silos, like these blind men we only see a little part that we touch — not the ‘whole elephant’.”
“There are many advantages to integrating data from multiple sources, such as primary research, secondary research, and transactional and behavioral data, to mention a few. Each of these sources provides information about an organization’s customer base. If you can bring these sources together like pieces of a puzzle we can obtain a clearer picture about your customers. When you look at data from only one source you look at the customer from a single perspective. Integrating data provides a more holistic view of the customer base, and more accurate information on which to base business strategy.”
“This enables the organization to increase sales by selling to the most profitable customers, and designing products and solutions that are more relevant to your customer. Insights from a holistic view can help prioritize initiatives that will most likely enhance customer loyalty, channeling your resources to those aspects of customer loyalty that will have the most impact on purchase behavior.”
Best Practices for Data Integration
“The integration process begins with understanding the data, gleaning it, and formatting it. First look for commonalities between the data sets, as granular as possible. Then you select a unit of analysis, such as a company, location sites, individuals, households, customer groups, or product groups. The unit of analysis that you choose varies by your business objective. For example, if your objective is to increase cross-sales, looking at aggregated purchases for the year will not be as helpful as looking at each purchase event: what was purchased and when. This way you can predict future cross-sell opportunities.”
“When you integrate data, you’ll likely have holes among certain data elements, where data may not have been captured consistently. You’ll need to determine what level of accuracy you’re willing to live with. Be prepared to spend some time to make the data sets ready for integration, or possibly use a smaller sample that is more complete for robust conclusions. After you clean and format the data sets separately, you may use a statistical package with merging criteria to merge the data sets. You’ll benefit by becoming familiar with data sets through iterative analyses, understanding patterns, and so forth. Then you can move on to mining the data, setting up your hypotheses, and analyzing the information.”
Broaden Data Sources for Customer-Centric Conclusions
“Focus on unlocking information from the data with a customer-centric persepctive: what is important to our customers, why is it important, how do customers make decisions, how do customers interact with us and professional colleagues and friends? To answer these questions, customer intelligence managers should broaden their thinking about the data sources to consider. In the past we depended on primary and secondary research, but today we have CRM systems with a wealth of purchase and sales and support interaction data, describing customer behavior. With the Internet we have data on customer visits, websites, etc. In addition to this structured data, we should consider unstructured data, such as in-person or online focus groups, and customer-generated data from social media (e.g. blogs, podcasts, online discussion forums, online communities, website visits). By integrating these data sources we’re able to be more customer-centric.”
Acting on Customer Insights
“One of the keys to success as a customer intelligence manager is to become a trusted advisor to your stakeholders. Develop a customer-centric focus for your work with internal stakeholders by understanding their business and objectives and challenges they face, and making them a partner in your research at the planning stages. When sharing your research findings, make sure your insights are believable, relevant, clear and concise, and that the insights make sense to the stakeholders. Maintain an open dialogue for joint ownership in the outcomes of your study, tailor your discussions according to their understanding, and make concrete recommendations. Assess your stakeholders and find your evangelists; if they trust you they’ll be the early adopters of your insights and take action on them.”
“Recently we analyzed a particular segment of our customer base, combining attitudinal and behavioral data. We started with purchase data, cleaning it, and looking for patterns. We identified different groups of customer behaviors, and found a certain group that was very profitable. We created a profile of this new segment: what differentiates them from others in their traditional segment, what do they buy, how and when do they buy. What we wanted now to understand is: why are these customers more profitable, what prevents other customers from following these behaviors, and what do we need to do to encourage other customers to behave more profitably. So we conducted some primary research via online focus group and survey technology for both qualitative and quantitative inputs. The data is now being used by our strategy team; the findings helped us understand customer needs and penetration opportunities, prioritize sales efforts with specific customers, and tailor our solutions, messaging, and channels to influence customers. We’ve been able to better predict which customers would likely buy certain products, and we’ve seen sales rise, and become more efficient in managing the business.”
Don’t turn a blind eye to the business results you could reap by fully utilizing your customer data. And remember to keep a customer-centric focus for outside-in thinking and sustainable payoffs through dramatically improved customer experience.
Access the entire interview at Using Data Integration for a 360-Degree View of Customer Experience (23:15) at BlogTalkRadio.com/customerexperience. Also look for the Cisco interview: Untapped Gold Mines in Customer Experience Data.
Contact the author to find out how to customize these tips to your situation.
Click here for podcast version: Customer Experience Data Integration for 360-Degree View of Customer Experience (7:17)
Click here for print version: Customer Experience Data Integration for 360-Degree View