Hearing the customer through data — reshaping and evolving CX
Powerful new technologies and digital solutions are making it possible to translate accessible big data into valuable ‘small’ data: useful pieces of intelligence you can use to improve processes, personalise services and offers, and make CX operations more efficient.
Connected customer journeys, next best actions, and hyper-personalisation are great CX aspirations that data analytics capabilities promise to make possible. However, as this year’s findings reiterate, customers still want minimal effort and ease of resolution when they deal with your organisation. Don’t lose sight of this when determining which data to collect, and how.
Start by imagining yourself as your own customer. What’s the most straightforward route to where you want to be? How can you make that happen? Keep listening to your customers so you can adjust what you’re offering to meet their demands.
Data, data everywhere … analytics the missing link
It’s not the lack of data that’s a problem. Untangling what you have to get to, what’s relevant, and what’s useful is what many organisations are struggling with.
Data analytics has been identified as the main driver of CX and customer satisfaction for the last four years, yet this year only 13.5% of organisations rate their current capability as optimal. For many, cross-channel data analysis is limited, so it’s difficult to connect customer journeys and get a consolidated view of CX.
Legacy systems aggravate the problem, as these platforms don’t communicate or share information with each other easily. Regulations governing the use of data also add a level of complexity in designing analytics systems with the right level of security for using and sharing customer information.
Use customer intelligence to make decisions that generate change
To address these issues effectively, you need a solid CX strategy that’s based on a well-defined understanding of what you want your analytics systems, processes, and technology to achieve.
Data analytics should drive decisions and change in the organisation. Almost every interaction is data-driven and most customers know you’re collecting their information as they transact with you. What frustrates them is when you don’t use it to make their lives easier.
Before you implement anything, be clear about what it is you wish to achieve, or you’ll be creating, rather than fixing, problems. Assess where you are, where you want to go, and the best way to get there. Look at what you currently have in place. How are your people and technology resources being used? Could they be better used elsewhere?
Go straight to the source(s)
Analytics starts with data, and we’re all familiar with the ‘garbage in, garbage out’ concept. Given that quality of input determines quality of output, consider which sources of data will be most beneficial to your analytics models and what you want to achieve.
Use voice of the customer programmes as part of an ongoing cycle of change and innovation. Disruptive organisations are getting their customers to test everything from new products and services to revised CX models, and they’re using the feedback to refine what they’re offering to better suit customer needs.
Venture beyond traditional data-collection methods to gather ‘silent data’ – things the customer doesn’t do or say that give clues to what may be causing churn or abandonment. Many customers won’t complain to you directly, so monitor social media and consumer platforms to gauge customer sentiment more accurately.
Employees are another valuable, but often under-used, source of information on customer desires, demands, and frustrations. Incorporate voice of the employee feedback into your data analytics strategy to capture this valuable intelligence.
It’s concerning to see that organisations are neglecting to gather data on transactions that take place on digital channels. If you’re not tracking these, you’re missing out on insight into the customer journey that will help you understand the impact these channels are having on CX – not to mention return on investment and cost to serve.
Digital channels may have been pitched as cost-savers but if they’re not being used effectively they could actually be contributing to higher costs in the form of increased customer queries and busier agents on the phone or in branches.
Small data, big impact
Big data is a big focus, but small data is also important. Remember that data is information about a person, so make it personal.
Customers set their own parameters and it’s important to take note of these. Pay attention to things like contact preferences – don’t send text messages if they’ve said they only want email.
Connect the dots by tracking simple things throughout the customer journey, like the customer’s name. Is this carried across in every interaction? These simple details demonstrate respect and build customer trust and loyalty. They’re also critical building blocks for hyper-personalisation.
What often makes these seemingly simple tasks such a massive headache is when the data used on different platforms isn’t structured in the same way. This could be something as basic as the way dates are formatted, for example: the data is correct, but it’s technically inconsistent. Or some systems may use codes that need to be translated into text for the data to be of any use. These issues must be addressed as part of your systems integration strategy, or you’ll be missing out on important data sources and links, and/or run the risk of data integrity issues. Crafting a data design methodology that can be applied across all data sources is a solid starting point.
Align the organisation to a customer-centric view
If your organisation isn’t aligned internally, you won’t have a chance of working with data effectively or understanding analytics thoroughly.
The success of your data analytics strategy hinges on how effectively you can gather and share information throughout the organisation. You need to augment standard service-based data with customer intelligence to help you see relationships between data. Identify predictable patterns and communicate this information effectively so it can be used by customer-facing teams and incorporated into quality management and training processes.
Take your employees on the journey so they know what it is you’re trying to achieve and how to promote new channels or services to customers. Keep third parties in the loop, too – tell your partners and vendors what you’ve discovered so that they, too, can deliver according to your customers’ expectations.
Where to next?
While data analytics capabilities are not yet fully embedded in CX, we expect to see an increase in data-driven CX in the next five years.
Data collation and data mining still rely heavily on human algorithms and questioning. Cognitive learning, machine learning, automation and artificial intelligence (AI) will start to change that. Machines will be taught to gather data and look for patterns and relationships that can suggest next best actions based on intelligent learning. They’ll be able to both predict the question and supply the answer.
Analytics capabilities will become more sophisticated and data sources will grow. Regulations that govern which data you’re allowed to collect and keep, and how you use it, will require constant vigilance.
The way organisations interact with data will change dramatically. What’s important is being able to use what you have in order to make continual adjustments to satisfy changing customer demand.
CX analytics infographic
See the top CX analytics trendsDownload the infographic
Recommended for you