Telcos are at an inflection point. For years, they’ve faced mounting pressure from better-funded, more innovative tech competitors, and seen a return on investment, profits and market share slowly dwindle.
When the pandemic hit, that pressure increased again. Suddenly, telcos were at the center of our lives; for many, the only means to connect with the outside world. And while leading operators handled that admirably, the crisis threw the reality of changed customer expectations – and the need to accelerate digital transformation to address them – into stark relief.
In such a volatile economic environment, it’s time to think critically about how telcos re-engage customers and reclaim the market. McKinsey lists ‘approach to customer engagement’ and ‘ability to leverage data’ as 2 of its 5 focus areas for telcos. Building strong personalization strategies satisfies both.
What to expect from this eBook:
Here at Intent HQ we believe how important it is to write good code. Why? First, because writing good code is much cheaper and more fun than writing bad code. Second, because if you write good quality code chances are that the product you are building will be much better. Third, and more important, because writing good quality code is what we are supposed to do: after all, we are getting paid for doing our job well.
Intent HQ unlocks hidden customer insights that activate more effective campaign targeting and provide a better customer experience.
Life is a digital experience for most customers. Big as it already is, the importance of customer data continues to grow. We are told that “data is the new oil.” Some of the largest enterprises on Earth are founded on data such as Google, Amazon, Alibaba, Facebook, Netflix, Salesforce, Microsoft, and Oracle. Many of these big tech firms didn’t exist 25 years ago, making their success astonishing.
Conducted in the spring of 2022, Intent HQ’s global study is the first to map consumer attitudes about data privacy with research into telco marketing practices. It highlights the disparity between attitudes towards using consumer data and beliefs about customer expectations.