How telcos are using behavioural science to drive relevance and increase revenues? - The EE

How telcos are using behavioural science to drive relevance and increase revenues?

There’s a widening disparity between truly personalised, relevant marketing communications and run of the mill, superficially personalised experiences. Behavioural science can enable brand owners to adopt a privacy first approach to engaging in truly personalised and relevant marketing communications, at a time when 76% of consumers say that being treated as an individual plays a key role in their consideration of brands. 78% of consumers also say it makes them more likely to repurchase, with the vast majority agreeing that the more personalisation they see from a business, the more loyal they feel, says Sharifah Armirah, chief client officer, Intent HQ.

In highly saturated, poorly differentiated industries like telecoms, financial services and utilities, where customer decisions are frequently price based, having the ability to truly personalise marketing communications can make a significant difference to long term customer retention rates. Large and potentially hindered by legacy technology, brands in these sectors can struggle to incorporate new, innovative data into their campaigns or to drive the incremental gains that are critical in such a saturated, price-sensitive and competitive market. Behavioural science could hold the answer, giving highly competitive brand marketers a cost effective and repeatable way to increase their customer engagement and conversion rates.

For instance, using a behavioural science approach, it is possible to identify and reach new, high value audiences, upsell products and services and increase customer value. By re-defining customer segmentation with the creation of data-driven microsegments, new variables that determine future buying behaviours can be uncovered. This was verified in two recent campaigns conducted for tier one telcos one in the UK and one in North America. In each example, the client was able to identify new and profitable audiences, exceed target campaign conversion rates, improve upon average campaign performance benchmarks and generate a higher than predicted ROI. Very importantly, they also avoided making some serious mistakes when it came to identifying exactly who their target audience was. More on this later.

Key to achieving these campaign outcomes was having the right data mining technology, systems that are capable of leveraging AI to abstract the real human meaning of observed behaviours from the behaviours themselves underutilised customer datasets like telco weblogs. From amarketing standpoint, weblog data is a typically undervalued customer data set because it is extremely difficult to use. It is vast in scale (consisting of multiple billions of rows) and regarded as highly sensitive.

When armed with the right technology, new behavioural patterns can be identified within weblog data that can supersede traditional, preconceived ideas of their most relevant campaign audiences. Rather than making assumptions, brand owners can be pushing the frontiers of cognitive understanding through digital footprints and doing so in a respectful and valuable way for all parties. However, a lack of access to the right data and technology means many will resort to ineffective ‘spray and pray’ targeting methods.

The problem is a long standing one. Diversity and inclusion sensitivity has become more prevalent, but on the whole, marketing has tended to rely on using familiar stereotypes and this alienates consumers. People want to be recognised as individuals and the target audience often isn’t who the marketers think it is.

Take this example of another real campaign, whose original targeting approach amounted to little more than guess work led by stereotypes. The client thought their customers for a roaming service offering were millennials who were video streaming and exceeding their data plans each month. They were about to launch with creatives showing this millennial user and it would have been totally inappropriate and potentially alienated the real consumer. Behavioural science data showed that the real primary audience was consumers aged 55+ who were using their mobiles for listening to podcasts and music they weren’t interestedin unlimited data packages because 97% of them were not exceeding their allowances.

In highly commoditised markets, having the ability to identify new markets based on consumer values and lifestyle preferences cannot be underestimated. Brand owners need to “think differently” about creating sustainable, customer-centric growth particularly in the face of an intensely competitive, rapidly-commoditising market. At times when brand and product differentiation is difficult and where customers are increasingly scathing when it comes to wastage, being relevant is key.

Sharifah Armirah

Most personalisation efforts are hamstrung by the quality of insights possible with the available data. The answer isn’t to collect more data. It’s to apply AI to the data you’re already collecting in order to understand its real human significance, the meaning of observed behaviours from the behaviours themselves without compromising on privacy.

When armed with the right behavioural data and analytics, our telco clients could unlock an infinite number of microsegments and target customers with very carefully curated offers. This in turn maximised revenue growth with greater customer engagement and conversion rates.

Businesses that can achieve true personalisation and close the gap between superficial targeting and a deep understanding of consumer behaviours will be tomorrow’s biggest winners. They’ll interpret new and better insights from richer sources of data and have the power to activate those insights for improved commercial outcomes growing revenue by reaching new audiences and cutting churn by delighting existing customers.

The author is Sharifah Armirah, chief client officer, Intent HQ.

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