Customer experience continues to be an area that benefits from data-driven decision making. Whether its reducing customer handle times, improving operations, or increasing sales conversions with predictive analytics, data is playing an increasingly important role in delivering personalized customer experiences.
In a recent McKinsey & Company article, titled How Advanced Analytics Can Help Contact Centers Put the Customer First, the firm offers up the key characteristics of an analytics-driven customer service organization, including where companies are making huge gains.
But first, let’s look at where companies typically get customer experience wrong.
The article points to a lack of the right technology foundation as a key stumbling block to delivering data-driven experiences. Indeed, factors, including an entrenched IT team less open to change, rigid existing processes, and legacy technology, can all contribute to lower analytics adoption. Disconnected data is another problem. Most companies are operating customer channels, like the web site and the call center, in silos. Finally, the inability for employees—especially front-line call center agents—to effectively turn data insights into actions that improve customer engagement is a missed opportunity for companies.
To help overcome these common challenges, the McKinsey article provides five “key traits” of an analytics-driven customer service organization that can help any company. Take a look:
- A clear vision and strategy: The good news for customer service and contact centers is that analytics solutions are delivering impactful benefits. Having a clear vision of the operational gains you want to make and a strategy to improve areas like average handle time, call volumes, and sales conversions are keys to long-term success.
- An agile organization with internal analytical capabilities: Make sure you have the right talent in house. This includes not only data scientists, but also generalists and business leaders that can help communicate the benefits and drive adoption of analytics-driven decision making.
- Platforms and data sources: Contact center analytics should support the overall organization’s business strategy and goals. According to the article, this requires best-in-class data governance, data or IT architecture, and infrastructure and data security frameworks. Data lakes and cloud data integration platforms are ways that today’s leading companies are pooling the extremely valuable customer data that call centers collect on a daily or even minute-by-minute basis.
- An ecosystem of partners: Look to partners to complete the picture. That’s the advice in the McKinsey article, which points to the fact that very few companies can internally source all the data they need for data-driven decision making.
- A culture of objective decision making: Today’s leading call centers factor data into virtually every decision they make. This includes “analytically driven hiring, targeted coaching, and performance-based bonuses,” according to the article.
With the right vision, strategy, capabilities, data sources, and culture, you can reap the benefits of the analytics-driven call center. According to the article, the benefits include reducing average handle time for agents, reducing call volumes, proactively enhancing network resilience, and improving service-to-sales conversions.
For more insights, including a deeper dive on business use cases, read the complete McKinsey & Company article.