There’s no question that data analytics can improve customer experience but to what extent depends on how well a company turns the data into actionable insight. Sarah Wray looks at some interesting and perhaps unexpected examples of success.
Using data analytics to improve customer experience is no longer a nice-to-have or an option for approaching the problem. It has become one of the core principles of customer-centric businesses.
Big data can be hugely helpful in determining what customers need; how they are shopping for and using your products and services; the problems they experience and how you can help them; how they feel about your company; and what they tell their friends. It can also provide important market and competitive intelligence. And it can do this at dramatically lower cost per unit of processing power than traditional technologies.
A study produced by the MIT Sloan Management Review and Capgemini Consulting found that companies that effectively deploy big data analytics, along with social business, mobile access and other digital enablement platforms, were 26 percent more profitable than their industry competitors, generated 9 percent more revenue through their employees and physical assets, and enjoyed 12 percent higher market valuation ratios.
When looking for examples of how to get data-driven customer centricity right, it pays to cast the net far and wide – you might be surprised at some of the companies offering inspiration.
Skype gets closer to the customer
A fundamental theme of our series of free how-to guides is that IT and data must enable businesses to become far more agile. Neil Ward, Vice President and General Manager, Skype, understands this very well:
“Proximity to the customer is part of the daily routine – there isn’t a minute in the day when Skype isn’t connected to its customers asking questions about products, product features and policies,” he says.
“So, the real distinction from the traditional players is that the time to market for an idea or a business case is short-circuited by a factor of at least ten,” Ward adds. “Traditional players are not as attuned to their customers and have become more of a wholesale infrastructure rather than an intuitive customer play.”
He goes on to describe how Skype quickly incorporates feedback.
“Actionable plans come out daily and we even have to be careful not to have too many,” he says. “These are coming from direct input from customers via old channels like email, but also via the community and social media. A senior executive can stop a product from being developed, but has to justify why. Otherwise the product manager goes back into the infrastructure to build the product. It isn’t the other way around.”
Sephora’s omnichannel approach
Ahead of his participation in the panel Cutting-edge strategies in data-driven customer-centric innovation at our Digital Disruption event at the end of 2014, Vincent Boon, Co-Founder & Chief Community Officer, Standing on Giants, told us where he’s seeing the innovation happen.
“When we look at the makeup and beauty brand Sephora, we can see they have put a lot of attention on how their customers interact with them, what their purchase patterns are, and where the touch-points are with the customer in an online as well as an offline environment,” he says.
Sephora has brought these online reviews onto the shop floor by allowing their customers to scan, through their mobile phone, any product on offer and immediately see and read customer reviews of it. Similarly, any customer shopping in a Sephora shop can, through their own mobile device or an in-store iPad, ask for advice on products from the online community.
“This fantastically integrates how a customer shops at Sephora and blends the online and offline world of the customer,” Boon explains.
In addition this approach provides data about customers’ purchasing processes that would not otherwise be available, enabling continued enhancements to their experience.
The right formula
A Formula 1 racing car is a data-generating monster. During a race McLaren’s two-year old Mercedes produces about 750 million numbers, from 120 sensors, in real-time. Newer models generate more. The data is sent to the garage then the factory, where the car evolves every two weeks.
Between races, it becomes faster as things are added, but the information is also analyzed to develop tactics to beat the competition.
“We think there’s a lot of hubris about big data – we don’t aim for big data, we aim for intelligence. We rephrase the question – what data do you need to get the predictive intelligence to run your business? When you understand that question, you often realize you don’t need data warehousing and storage people are fretting about at the moment,” said Geoff McGrath, who leads McLaren Applied Technologies Limited when he was interviewed for a BBC radio program.
This approach is useful for service providers too. Analyzing how new devices interact with the network and addressing emerging problems, for example, can result in much lower customer care costs and happier customers. It might not be as glamorous as Formula 1, but it helps to drive efficiency and profitability, for the benefit of your customers and shareholders
Robi Axiata tests the waters
Robi Axiata Limited, a joint venture of Axiata Group and NTT DoCoMo and the second-largest mobile operator in Bangladesh, wanted to ensure it was asking the right questions, in the right ways, to improve customer experience and increase revenue using analytics. So instead of buying an analytics platform, the company decided to explore global standards and examples of how a big data project should be approached. It used TM Forum’s Big Data Analytics Guidebook to provide a set of such examples to establish proof of concept.
“We have seen a huge improvement in our NPS (net promoter score) after we started taking actions from customer experience analytics,” says Ahmed Saady Yaamin, Vice President, Business IT, Robi Axiata. “The idea is to focus on the actionable, granular insights to find out the root causes that create customer dissatisfaction and then to take proper action, and continuously monitor it.”
“As an example, last year we started a special focus on handling customer complaints regarding value-added subscription charges,” Yaamin explains. “Our analysis revealed that at some point, a customer subscribes to a value-added service and then stops using it over time. Since it’s a monthly subscription, they are being charged automatically. We found those subscribers and gave the charge back whenever there was a complaint logged. This has dramatically improved the NPS score.”
How to make it happen
Here are some tips and insight into adopting a successful data-driven strategy:
- Smart companies start by working out what they are trying to achieve, then look for actionable, not just interesting, data.
- Even for the best companies, analytics and customer centricity is a moving target as the number of ways of interacting with customers continues to expand and services are increasingly delivered through partnerships. Also, customers’ preferences, expectations and behavioral changes, along with advances in technology, can cause huge market shifts. You need to constantly experiment and iterate, and measure your progress continually against its contribution to your goals
- Any foray into big data analytics must consider the privacy of the individuals whose data is being analyzed. One of the fastest ways to lose customers’ trust is to expose their private information or inadequately protect it.
- Take advantage of all the help and resources available to you, such as the collateral and activities offered by TM Forum, including big data use cases, the customer experience lifecycle model and step-by-step how-to guides. These tools are developed and continuously evolve through the joint efforts of thousands of engineers, architects and experts across many disciplines within our unique Collaboration Community.