Sponsored Feature

Using AI and machine learning to drive customer-centricity in a connected world

Sponsored by:

Wilson Raj, Suzanne Clayton

Today’s customers are more savvy and demanding, and frequently switch across channels. Meanwhile, average revenue per user continues to fall across global regions as over-the-top vendors like WhatsApp, Viber and Apple’s iMessage continue to gain market share and erode the traditional telco business.

Communications Service Providers (CSPs) must move marketing and customer care to digital channels, which presents both an enormous challenge and a huge opportunity to use all this new data and use AI to take the customer experience to a new level.

Also, as video consumption on mobile devices grows many providers are moving to quad play: broadband Internet access, telephone, television and wireless. So there has never been a greater mandate for CSPs to be truly customer-centric.

This leaves CSPs struggling to answer three vital questions:

  • How can I better know my prospects and customers?
  • How do I keep them engaged and loyal to my brand and services?
  • How do I maximize budgets to keep both customers and management happy?

How can I better know my prospects and customers?

One of today’s biggest marketing challenges across industries is the proliferation of channels. That doesn’t just mean web, mobile and brick-and-mortar stores, but buyers can be found everywhere from print media to social media, broadcasting to podcasting. What many regard as one channel – mobile – is actually several channels at once.

A recent Econsultancy study reveals that true customer recognition – while touted as a critical priority – is elusive.

When customers feel they are not being recognized across channels, it can lead to churn and decreased satisfaction. Customers are permanently connected, and they expect to be treated as unique. In the vast sea of messages and offers customers receive each day, they have only time and patience for content that is personalized and relevant. Social media has empowered customers to expect nothing less and has also given them a forum to broadcast a negative experience.

The good news, though, is that with all that bouncing from channel to channel, consumers leave many data traces, and all that data adds up to become big data. By analyzing these big data traces (structured and unstructured, residing within the company walls and outside of the company), marketers can get to know their customers with an unprecedented level of detail. For example, by using natural language processing techniques like text analytics, CSPs can better understand how customers feel and why.

These insights can be fed into various customer care and marketing decisions and programs.

How do I keep customers engaged and loyal to my brand and services?

Marketing experts know they need to send the right message at the right moment to the right customer through the most effective channel, and the profession has come a long way in its ability to do just that.

By moving customer interactions to digital channels, marketers will gain a wealth of data. CSPs need to make sure they are not just cutting costs, but are also modernizing their marketing and care operations to have a single view of the customer. Then they must be able to interact with the customer in real time.

Marketing and care functions are most effective when they answer immediate needs. For instance, a telco can offer a data renewal opportunity to a traveling customer who is using his device to stream video content, but is up against his data limit. By using real-time analytics like machine learning, CSPs can be with their customers wherever they are and programmatically intervene to provide exactly what the customer wants or needs at that exact moment. We are seeing leading companies like Telefonica make these types of advances and beyond with their announcement of Aura, a cognitive brain, at Mobile World Congress 2017.

How do I maximize my budgets to keep both customers and management happy?

This is perhaps the most difficult to answer. You have to keep customers happy, and to get them to buy your product or service. But it’s just as crucial to make sure that marketing efforts align with the company’s overall strategy to maximize efficiency and profitability.

Smart analytics make sure that organizations remain customer-centric while picking the best choices for the organization. Surprisingly few marketing organizations are equipped to do this.

A key component to this is mapping and optimizing the customer journey. Knowing the actions your customer will take across channels and what decisions they will make and why is crucial to maximize the customer journey. For many CSPs, this is nearly impossible and is often attempted via manual processes using incomplete data – which no way to truly measure attribution and conversions. By applying AI components – particularly optimization – marketing and care organizations can identify the best action. Optimization involves deciding the best use of limited resources given a set of constraints through maximizing desired factors and minimizing undesired ones. It can be used for determining the best campaigns or best action in a care situation, or for charting the customer journey.

The customer journey and beyond

Consumers today demand to be recognized and treated consistently, whether they are visiting the website of the CSP, visiting a retail store or chatting with a service representative.

To meet such expectations, CSPs must have effective technologies and processes in place to not lose direction when tracking, designing and measuring the customer journey.

One customer view across all channels. Omnichannel goes far beyond just email and web. CSPs must link what customers are doing on digital properties with what they’re doing elsewhere, such as in the store or with the contact center. A single view of the customer allows CSPs to offer a personalized, relevant customer experience based on past interactions using machine learning.

For example, telco stores are still seen as an important way to interact with the brand for cross-sell/upsell and to prevent churn. Some leading CSPs are using insights from analytics to transform stores into a digital experience space. A customer going to a Telenor store can check in beforehand and receive a personalized experience via modern and engaging multitouch signage and kiosks.

Data freedom and protection. Marketing and care functions must access their data when, where and how they need it, so they can use it to make better and faster decisions. They must have data management and analytics capabilities to stitch online and offline transactional data with CRM data and further verify that each online ID (cookie, IP address, device ID) is mapped to a verified individual. They must also protect and govern their data or be out of compliance with GDPR and other privacy regulations.

For example, CSPs are modernizing their IT and data management infrastructure as part of a core component of digital transformation. Most have implemented Hadoop, and many are adopting machine learning for analyzing big data including CDRs, data from set top boxes, geolocation data, web data, social media data and other data for key customer insights. They are also focused on securing customer data and a creating a more robust data governance program. Sprint is currently going through digital transformation and moving to one centralized, flexible and governed analytics platform for better decision making.

Guided analytics. Marketing and care functions must look to embedded AI components to make digital channels smarter and more efficient. Automatic micro-segmentation and machine learning algorithms deliver more context to each customer interaction.

For example, CSPs providing video services are making data leaps and bounds by capturing viewership data and using machine learning to intelligently segment viewers, make content recommendations, understand root cause analysis of poor video quality and predict content performance. A leading US satellite provider is seeing the benefits of this through decreased churn, decreased programming fees and greater customer satisfaction in their entertainment division.

Performance insights. Marketing and care functions must see vital measures of their success – not only which activities are working, but what content performs best, which customer segments to focus on, and what is the best sequence for an individual customer’s experience.

For example, many CSPs are using analytics and machine learning to gain insight into the customer’s network experience, do better network planning and improve the overall performance and quality of service. Telecom Italia and many other CSPs are combining analytics with Hadoop to look at network transactions and the impact of certain apps on the network, analyze network congestion by geographic locations, cell tower performance by handset, etc. This data is then married with marketing and care data to enable the improvement of the overall customer experience.

Moving forward

Marketing and care functions must go beyond traditional web page views and clicks to know exactly why customers behave as they do in their different channels; what the characteristics of the most profitable customers are; and what digital interactions are successfully derived from the loyal and profitable relationship between organizations and their customers.

As we move into the next generation of telco, using AI and big data to uncover customer and business insights will be every brand’s most strategic weapon. The CSPs that thrive will use AI to optimize customer journeys and infuse it throughout their organization to serve customers quicker, better and take their brand experience to a new level.

To explore more, visit sas.com/ci


    About The Author

    News content collected from leading sources around the world by key TM Forum staff.

    Leave A Reply

    Back to top