Cheryl Ragland is an accomplished marketing leader with expertise in driving growth through innovative strategies, brand management, and digital marketing. Currently leading global marketing at Spirent, she previously served as CMO at Infovista and Global VP of Corporate Marketing at BroadSoft, overseeing comprehensive marketing functions.

In a recent conversation with Global Woman Leader Magazine, Cheryl shares her insights on the role of AI in reshaping customer engagement strategies within the telecommunications industry over the next five years. She also addresses the balance between hyper-personalized marketing, data privacy, consumer trust, and the challenges of integrating AI-driven insights.

Given the rapid evolution of AI technologies, how do you foresee AI reshaping customer engagement strategies in the telecommunications industry over the next five years? What specific AI-driven innovations do you believe will become essential for staying competitive?

The good news here is that the telecommunications industry already has a jump on using AI. We recently published an eBook called Bracing for Impact: How AI Will Transform Digital Industries that looked at current and future AI use cases in telecom.

It details how telecoms have been tactically employing AI to help with internal processes including anomaly detection in network operations and external, customer-facing systems such as chatbots for several years.

The opportunity to reshape customer engagement strategies comes from building on this foundation via automation. For instance, with a chatbot powered by a large language model and machine learning, AI classification and predictions can play a key role in enhancing customer satisfaction by anticipating questions and providing options – such as a choice between different data plans – for customers to easily act upon.

In the context of AI-powered personalization, how do you balance the need for hyper-personalized marketing with concerns about data privacy and consumer trust in the telecom sector?

This is a critical issue that boils down to respecting your customer. Adhering to two best practices can help: always getting consent from your customers and only collecting the data you need.

We should strive to proactively ask customers to opt in to sharing their data, rather than collecting it by default. Once we have this permission, we then need to maintain that customer’s trust by only capturing the data we need in order to serve them.

For example, if browsing history provides enough insight to present just the right offer at just the right time, do you really need to collect location data as well? Being selective in this way not only helps tailor your message to your customer, it also pays dividends in maintaining that customer’s trust so they’ll be open to other offers in the future.  

How can AI-driven insights and predictive analytics be used to gain a competitive edge in the telecommunications market? What types of data are most valuable, and how can AI help in transforming this data into actionable strategies?

This may be the most exciting aspect of using AI in telecom today, because it brings together both network optimization and customer experience.

AI can be trained with vast amounts of historical network data to model and accurately predict anomalies, alerting teams to threats so they can proactively mitigate them. It can also learn from digital twins in large-scale simulations to simplify cell load estimation, spectrum utilization and traffic routing. But that’s just the beginning as 6G evolves toward future cognitive networks and full-scale, intelligent automation.

The resulting efficiency in the network can then lead to higher quality service and customer satisfaction to up telecoms’ customer experience game. AI predictions and classifications can then tailor service offerings to each customer’s unique preferences.  

What are some specific ways AI can be used to streamline marketing operations and enhance efficiency within a telecommunications company? Can you discuss potential challenges and solutions in implementing these AI-driven processes?

One of the first lessons of AI’s rollout to date has been its efficacy as a tool to help skilled professionals complete tasks more efficiently, with less time spent on low-value activities.

This is a perfect fit for marketers. For Spirent, as a global enterprise that helps clients stress test their systems before they go live, it has meant being able to tailor specific campaigns in various regions with translation completed on the fly.

The challenge, however, is that machines still don’t have the nuance or level of sophistication that comes from spending a career focused in a specific area. Marketers must make sure our prompts for gen AI content are specific and on target, and give the output a human “sniff test.” The bottom line is we can’t – and shouldn’t – put our marketing campaigns on autopilot. 

What are some of the most significant challenges you anticipate when integrating AI into existing marketing infrastructures in telecommunications? How can companies overcome these hurdles to ensure a smooth transition and maximize AI benefits?

Another big lesson that’s emerged with AI’s early adoption, including in telecom marketing, has been a relearning of the truth that if you put garbage in, you get garbage out. One of the biggest challenges for marketers right now is making sure the data they use to power their new AI tools is up to the task.

That not only means being able to aggregate and integrate data for AI analysis from disparate legacy systems, but making sure that data is accurate, clean and usable by today’s more sophisticated tools.

To overcome this challenge, don’t try to boil the ocean. Start small, with a well-defined and focused area or task – A/B testing of a campaign with variable subject lines, copy and visuals comes to mind – and then expand from there, using the lessons you learn along the way.

AI has the potential to enhance creativity in marketing. How can telecommunications companies harness AI to foster innovative and creative marketing campaigns that resonate with today's tech-savvy consumers?

To me, one of AI’s most compelling uses so far has been as a tool to brainstorm and elevate existing marketing content. Rather than just use a gen AI engine to create copy from scratch – which can still be hit or miss – the tool can give marketers options for the campaigns they’re working on already.

For example, pairing AI’s content generation and optimization capabilities to learn what color schemes, messaging and delivery formats resonate best with different audience segments can help take the guesswork out of campaign development.

Then, once that campaign is live, AI can continually monitor customer interactions and suggest alternatives if a particular aspect isn’t performing well. In this sense, AI can be a marketer’s round-the-clock creative assistant, suggesting fresh new ways to connect with customers when you’re out of ideas, no coffee needed.