Getting a strong return on investment for your marketing activities shouldn’t be just about signing telecoms customers up for higher-tier plans or new services. In this sector, ensuring existing customers also feel engaged with their provider is also vital for long-term success.
Those that don’t have a personal connection with a telco aren’t likely to stick around when the time comes to extend their contract, let alone increase their spending. Therefore, taking steps to improve this relationship by delivering the most relevant experience at every stage of the customer journey is essential.
To do this, an effective customer analytics program is a must. If your efforts in this area aren’t taking into account a complete 360-degree view of the individual, you’re likely to be missing key indicators of what matters to them. Without this, you won’t be able to provide the truly personalized experience that today’s customers now expect.
Customer experience (CX) matters more than ever to businesses across all sectors, but it’s especially important for the telecoms sector. Brands are finding it harder than ever to stand out on price alone, so it’s vital they can offer relevance and personalization across all touchpoints in order to engage and delight users.
At the same time, customers are more discerning than ever. Research from PwC, for example, suggests that up to a third of consumers around the world will abandon a brand after just a single bad experience, while in the US, 59 percent will walk away after several bad experiences, even if they had previously been pleased with the business.
Given that it costs as much as four times more to secure a new customer as it does to retain an existing one, this can be very costly.
So how do firms actually go about translating their analytics activities into an improved CX strategy? Looking carefully at their behavioral data gives you great insight into areas such as personality traits and interests, but with the right tools, you can go far beyond the sort of superficial high-level segmentation offered by traditional CRM-based analytics tools.
When it comes to churn, an effective customer experience analytics model can help identify any particular risk factors that may increase their chances of leaving. For instance, a more traditional way of using data may be to identify people who are regularly exceeding their data cap in order to target them for an upsell.
But what about people who aren’t coming close to their limit? Could this suggest they aren’t engaged fully with their provider? Not necessarily. Customer relationships with their devices are very personal and complex.
To conclude that such customers are not engaged and resort to a reduced plan rather than risking losing them altogether just leaves money on the table. The secret is to know your customers better; their interests, usage patterns, payment history etc and bring all these together. By understanding the relationships between each data point, you can make sophisticated decisions about your customers that lead to more personalized and successful response mechanisms.
Advanced analytics are now being used to create a wealth of insights, enabling churn models to be more sophisticated than ever and identify patterns earlier from billions of data points. They are informing decisions on what offers would deliver the most relevance to a customer at risk of churning, what creative would best match their personality, and via which channels will have the most impact in creating a fully-personalized brand experience.
A good analytics platform should also be able to provide this insight to everyone within the business. By making insights accessible and user-friendly, this breaks down some of the silos that can create bottlenecks between marketing and business intelligence functions and help build a company culture that’s more data-driven across all areas.
However, this also can’t guarantee a strong CX performance, especially if the message isn’t getting across to the customer in the right way. Saying the right things is only a small part of a successful CX strategy. Other essential elements include when you say it, as well as the medium you choose.
For instance, on a simple level, knowing when to send a message to a user who’s nearing the end of their contract matters. You don’t want to wait until they’ve already started comparing competitors, but act too early and it will already be forgotten by the time they come to make their decision.
The ability to learn from the behavior of thousands of past customer contract renewals, singling out the ones that have the closest match to customer profile and situation, and identifying those that resulted in a positive response can inform the next best course of action, including when you get in touch.
At the same time, how you get your message across matters. Some people won’t react well to SMS messages or push notifications on their device, for example, as they may see it as intrusive. Others may automatically send email messages to their spam folder. Looking closely at these traits helps ensure that the communications you send and, by extension, the experience you offer, isn’t just relevant, but also timely and likely to be welcomed.
For example, using weblog data, we were able to identify who has interest in print (broadsheet newspapers, magazines, etc.) within a qualifying step up target, and that direct mail audiences had 37% higher incremental takes than the BAU randomized target subset. This enabled us to target campaigns much more effectively and deliver a higher return on investment.
This is just one example of the essential role advanced customer analytics plays in telecoms marketing campaigns. Telcos that are able to harness this effectively therefore stand to enjoy much better results
Find out more about the role of customer analytics in telecoms and why it matters.
Image credit: iStockphoto/B4LLS
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