Pauline E. Ranger Progressive companies use data mining and sophisticated data collection to uncover hidden insights into their customers’ experiences of their products, brands, and services. Recognizing that business intelligence does not involve a set of algorithms that look at the same data in the same manner, hoping to find something new, they use tools and techniques to gain more insights and do so faster.
Then, they convert this information into natural business intelligence, which will help them take more decisive actions about product mix, marketing, and service levels.
Many companies use quantitative data mining techniques to identify trends in Customer Experience and determine the magnitude of problems or opportunities.
Marketing leaders who want to understand in-store merchandise execution and its impact on customer experience and financial performance typically monitor in-store merchandise execution by secret shops. They also track unit-level statistics and customer feedback.
These efforts can inform marketers about the effectiveness of merchandising and which units do not see the expected sales increase. These techniques do not give leaders the necessary intelligence to take corrective actions.
Marketing innovators use new tools and technology to enhance traditional quantitative data mining efforts.
Unusual approaches, such as advanced video analysis and “day in life” sketches, bring a new level of business intelligence. This allows leaders to forecast and prevent risks, challenge core assumptions, accelerate product or service offerings, and find and eliminate obstacles to delivering a positive customer experience.
Video Analytics
Video ethnographers use video to uncover the “unmet” customer needs and discover their experience.
Recent advances in video technologies and analytic techniques allow innovators to gain more profound and more systematic insights into their real customer experiences:
Video technology such as small, portable cameras, remote viewing and downloading, and the capability to tap into existing security camera configurations improve the data collection precision. It reduces the overall cost for the organization.
The ability to quantify results and to find deeper cause-and-effect relationships is improved by advanced approaches for coding specific events and conditions across thousands of customer observations.
Searchable digital databases allow researchers to report and find specific events more quickly.
These advanced video analytics techniques allow organizations to track the travel patterns and activities of employees or customers, identify bottlenecks within the service experience, and classify purchasing behavior to understand better where, when, and why a particular issue occurs.
Assume, for example, that you have marketing intelligence that suggests your in-store merchandise efforts aren’t generating the financial returns that you expect. Video analytics provides the intelligence required to pinpoint solutions.
In-store merchandising can change how customers move through a shop and the products they purchase. The analysis isolates factors influencing actual purchases and uncovers unintended consequences such as bottlenecks and low-traffic areas.
Employees are vital to maximizing the impact of merchandising campaigns. Audio and video can show that employees who engage with customers, make themselves visible during peak buying hours, and consistently reinforce marketing messages with customers… can convert more people into customers. Video analytics can help identify the causes of employee disengagement, such as staffing shortages, staffing choices, and staff training levels.
“Day in the Life Sketches
A new way to gain deeper insights into customers and employees is by creating detailed “day-in-the-life” sketches. These help articulate the “emotional experiences” of both parties, better understanding how they behave and think.
The techniques range from the low-tech to the high-tech. For example, video cameras are strategically placed and handheld devices that record experiences and events. The methods range from those that involve the “target” in a high level of involvement (such as recording and self-journaling) to those with a low level of involvement (such as checkpoint interviews and observer journals).
Data collected from sketches, like video analytics, is coded and analyzed to bring the experience of employees or clients to life. This can range from everyday experiences to unexpected and unique experiences.
Video analytics showed that your staff was not engaging with customers in the manner you had hoped to maximize your in-store marketing efforts. It does not reveal why employees choose their actions; these insights are crucial for developing solutions that stick.
Managers are distracted by competing priorities, which reduces their attention and time spent on in-store merchandise. Many managers feel their staff should spend more time with customers, but other tasks are more critical. Effective managers have developed a shared approach to leadership that allows them to make better decisions, anticipate problems, and respond more quickly. Manager training can increase the likelihood of having positive interactions with customers by focusing on these successful approaches.
Employees don’t feel comfortable approaching customers in the manner we have asked. The “Day in the Life” sketches created across retail units reveal three primary reasons for employee willingness to engage with customers:
It is normal to go beyond the call of duty to engage with customers
Reward and recognition programs directly linked to financial and customer service goals
Good fit for staff–individuals who have the disposition to engage with customers consistently
