3 steps to predict new TMT customer patterns beyond the numbers

 1. Go beyond static data sets to gain root-cause insights

TMT companies all collect vast amounts of usage data at scale: what consumers watch, click on, times of day, preferences, websites and ads that engage. But while data is collected across apps, phones, web interfaces and a myriad of digital touch points, many organizations are realizing data’s limitations – or soon will. As first-party data collection restrictions impact traditional data collection practices, and much of the data collected is unstructured, meaning open-text or rephrased, understanding the implications of the numbers is increasingly essential to business success. Now, new analytics technology enables TMT organizations to access insights into both operations and consumer behaviors to help deliver what every company wants – the root cause of their top challenges and opportunities.

Let’s look at an example that highlights the difference between traditional data and the impactful combination of both operational and consumer insights. In our work with a major utility company, we identified a spike in negative feedback about service call hold times. In an instance like this, standard data analysis might simply attribute the sentiment to time spent on hold and lead to strategies that speed customer service. Intelligent insights helped pinpoint the true root cause: a “green energy” marketing logo placed on the company’s website. This triggered calls that service agents weren’t trained to manage and resulted in long hold times as they looked for answers. In the end, a very different actionable strategy was identified: removing the logo of the non-existent service and training agents accordingly.

    2. Capture true customer voice to better define brand experience

When customer options for tech solutions, wireless service and streaming TV are overwhelming, winning the consumer vote must become about delivering satisfaction and enhanced experiences with your brand. To do that demands understanding the real voice of the consumer –not from single interactions, but across multiple touch points. Organizations must adopt an omnichannel consumer listening approach that brings together insights from sources like call center calls, chat data, traditional surveys and social media feeds to create a comprehensive view of perceptions of a company’s services, issues and products. The right insights into how operations are functioning and the ways that execution impacts consumer perception, behavior and preference can be the powerful, data-driven accelerator for a lot of critical decision-making. These can include strategies designed to boost digital and front-line operations, deploying artificial intelligence (AI) tools and customer service strategies that create better omnichannel experiences and build consumer loyalty. Inside of the organization, employee experience insights can better engage teams, improve manager effectiveness, help leaders make informed talent and business decisions, and enable the design of products and services that customers truly love.

    3. Cluster consumers into cohorts to scale understanding and engagement

Growing customer loyalty in industries dominated by incentives to switch streaming services, internet provider or wireless company requires targeting exact consumer preferences both at scale and cost-effectively. That’s just not possible without a deeper level of consumer insights that can enable true segmentation. Based on their preferences and behaviors, individual consumers can be clustered into cohorts – defined groups of consumers that share characteristics and traits. This enables behavioral segmentation, allowing consumers to be better understood and marketed to in larger volumes. That can be done with more personalized messaging and tailored offers for products and services. In turn, consumers feel heard and served the information and products that appeal to them.

In summary

Insights gained with the use of AI-driven speech and text analytics can now provide TMT businesses with extensive feedback. This feedback will help companies better predict consumer patterns to drive improved actions and outcomes. Things like sentiment analysis at scale and identification of themes, as well as the expended effort to reach consumers vs. conversion metrics, may soon be the new benchmark for success. And everyone from the C-suite to sales, customer support and the end consumer is going to benefit.