By David Ffoulkes-Jones
In tough economic times, with fierce competition in a commoditized market, nobody can afford to take customer loyalty for granted. It’s five to 15 times more expensive to acquire a customer than retain one, so customer retention should be a key focus for all organizations.
According to the Accenture Global Consumer Pulse Survey, we’re now seeing a “switching economy,” with $6.2 trillion of business for the taking this year, up 26 percent from 2010. Sixty-two percent of people globally changed their service provider in 2013 because of poor customer service. And yet 80 percent of customer service switching could be avoided by better resolution.
People leave for a variety of reasons: They find a better offer, they no longer feel valued, their issues are taking too long to resolve, or they simply want a change. It’s often the case that new customers are enticed with offers unavailable to existing ones, creating a certain amount of resentment in the installed base.
Read “The Three A’s of Customer Care” — Analytics, Artificial Intelligence and Automation – because The market has changed: Tough economic times, an omnichannel world, rising customer expectations, and increased competitive pressure.
Customer Care needs to change too.
So there are lots of factors at play, and it’s often difficult to determine exactly why customers defect. Difficult, but by no means impossible. And now, with the help of sophisticated analytics, we’re able to predict which customers are likely to defect so you can take preventive action.
The Mobile Challenge
To see the dynamics of customer churn, let’s take an industry with high levels of defection: mobile carriers.
Loyalty in the mobile arena is low, with Net Promoter Scores (NPS) trailing behind other industries. At any one time, 34 percent of customers are thinking about switching operators. When they change their handset, 58 percent of people will consider changing brand. (Source: WDS Mobile Loyalty Audit 2014)
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Mobile, like so many other industries, has become commoditized over the years. Coverage and network speed are now similar across all carriers, so different factors come into play. Customer service is now hugely influential when it comes to brand satisfaction and retention.
A big reason for people not switching is inertia. Only 44 percent of retained mobile customers are highly satisfied, and 26 percent say the only reason they don’t leave is that it’s simply too inconvenient. But as soon as a more convenient option comes along, especially if it’s combined with a better price, that inertia is soon overcome.
For mobile carriers, there are some key early warning signs of churn:
- An NPS detractor is seven times more likely to switch than a promoter.
- A customer who has contacted support more than twice in a six-month period is six times more likely to switch.
Age is also a vital consideration in this market:
- Customers under 24 are three times more likely to switch, even if they’re highly satisfied with the brand.
- Customer service is big factor for over 45s, with 82 percent saying it plays a very important role in their decision making.
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Know Your Customer
It’s clear that mobile carriers must move from price-based to value-based relationships, as do all organizations in a commoditized market. And that means getting closer to customers.
If you have a large customer base, getting close to each one is a challenge. Yet that’s the only way you’ll know if they’re likely to defect. Luckily, in the age of Big Data and deep analytics, it’s become a whole lot easier.
Text, voice and real-time analytics now allow you to build up a comprehensive profile of customer issues, sentiment and even personality type. The more you know about your customer, the better placed you are to make sure they remain on board.
Thousands of data points allow you to really understand the customer (age, location, spend, buying patterns) and their issues (regularity, complexity, preferred channels, time to resolution). You can then cross-check this information against previous defection data, evaluate the risk and take action based on detailed customer insight.
Analytics, A.I. and Automation to the Rescue
If customer service is the key differentiator, and the one thing that will prevent customer defection, clearly it needs to get better. But as better service has always meant higher costs, is it inevitable that you need to pay more to reduce churn?
Far from it. That’s because the increased customer insight you get from deep analytics can be combined with artificial intelligence and automation to deliver better service at lower cost.
Machine learning now means that service is refined and improved over time, so that agents can find solutions faster and more efficiently. Automated self-serve systems can also learn from every customer interaction, which means that customers get better, more accurate, and more personalized service, often without any human interaction.
And that’s hugely important in preventing defection.
According to the Accenture Global Consumer Pulse Survey, customers are increasingly frustrated with the level of service they experience: 91 percent because they have to contact a company multiple times for the same reason, 90 percent by being put on hold for extended periods, and 89 percent by having to repeat their issue to multiple representatives.
Bad Churn and Good Churn
It’s important to point out that not all churn is bad: Sometimes, there are customers you want to lose, because they’re low-value/high-maintenance, and actually cost you money to keep. This “positive churn” can allow you to cut costs and improve service to high-value customers.
The key to this is knowing exactly who you want to keep, and who you can afford to lose. And once again, that comes down to deep analytics and detailed customer insight.
Closing the Gap and Keeping the Customer
In the 21st century, customer loyalty is a war of attrition, with customers becoming less loyal over time.
Customer experience and loyalty levels are determined by the gap between customers’ expectations and reality. So organizations need to constantly focus on customers to keep those levels high. Regular small gestures are much better than a last-ditch attempt to keep a customer, by which time it’s likely to be too late anyway.
Analytics will play an increasingly important role in identifying people at risk of churn, and, combined with artificial intelligence and automation, will help organizations close the gap and keep the customer.
With $6.2 trillion to play for, customer retention is a high-stakes game. Those who harness the power of technology will play it well and reap the benefits.
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