Advanced analytics play an essential role in making a lasting first impression on potential consumers. The predictive capabilities supplied by machine learning technology further accelerate buying behavior by helping organizations know who to engage, what products or services to suggest and when to suggest them based on where each person is in the customer journey. Consumers will then have a clear idea for why they should purchase something based on how you have positioned it.
That’s the who, what, when, where and why of using advanced analytics to make smarter business decisions that can boost the bottom line, as explained in parts one and two of our three-part blog series.
However, part three is arguably the most important, yet most easily overlooked aspect of the customer journey: customer loyalty. It’s a well-known fact that it’s more financially responsible to try to keep customers long term than to be constantly chasing after new business. It’s also true that no customer journey is without its road bumps, and while advanced analytics certainly smooth out the infrastructure of consumer engagement, how an organization responds in its worst moments is just as important as how strong it is in its best moments.
In this last post, we’ll look at how organizations can use advanced analytics to nourish the cycle, so as to improve customer loyalty.
Know who you’re dealing with
As mentioned in part 1 of these posts, Garter analysts have advised organizations to look beyond demographics, and focus more on “personas,” which are created based on how certain customers behave. In that context, we meant more in terms of knowing the best way to engage with them, be it social media, email drip campaigns or something else. However, for the purposes of fostering customer loyalty, the word “behavior” takes on a much more literal meaning. For the sake of continuing the customer-journey loop, businesses actually need to concern themselves with how customers behave – as in, what makes them tick, and which pain points should you steer absolutely clear of.
Take the example of how pharmacy retailing giant CVS helps its customers. According to TechTarget contributor Nicole Laskowski, the company began creating “behavior groups” for its customers in an effort to improve support in contact centers. A total of six customer categories were formed. Simultaneously, CVS began “scoring” its contact center agents. The company then applied this data to predictive analytics in order to determine which representatives work best with specific behavioral tendencies of certain customers. The program was successful in that it reduced total call time, while also improving the outcomes of these calls.
The moral of the story here is fairly straightforward: Big Data aggregation parsed by prescriptive and predictive analytics can improve the health of customer relationships, and increase the likelihood that customers will come back.
The end game: A positive, panoramic impression
“Achieve the trifecta of a strong customer journey, and more importantly, a sustainable one.”
The above example is a specific case study of how a company used predictive analytics to achieve stronger company responsiveness. While the value here is undeniable, customer service is still only one leg of the customer journey, and fostering brand loyalty requires more than that. It calls for consistency across the board – smart branding, timely and appropriate offerings, anticipation of your customers’ pain points and more.
Real-time data aggregation and analytics used across all channels of your business can help you achieve this consistency. The resultant perceptions of your company will supersede good branding. It will be a reputation of competency, mindfulness, helpfulness and relevance that’s deeply embedded in organizational workflows, both internally and on the customer-facing end. It’s difficult to quantify the long-term benefits of these overarching impressions – but it’s safe to say that they’ll most likely enhance the sustainability of any business.
Remember, long-lasting customer loyalty is the ultimate goal, and the best way to achieve it is to continue to be useful and relevant to customers – as explained in parts 1 and 2 – but also attentive to their concerns, and responsive to their complaints. Only with these qualities combined can you achieve the trifecta of a strong customer journey, and more importantly, a sustainable one. Don’t leave this dynamic up to chance. Use powerful analytics and you’ll reap powerful rewards.
This is part three of a three-part blog series about transforming the customer journey with advanced analytics.