By Intent HQ’s Taya Vernon
These days, the main discernible difference between two telco brands is often the way they treat their customers.
We talk about enhancing the customer experience and improving the customer journey – but creating a real stand-out amongst competitors depends on developing a much deeper, more human-like understanding of customers than ever before.
Telcos know that this gold dust lies within the mountains of data they accumulate each day – calls, purchases, web visits, app usage, locations and social profiles – for example.
However, it’s all worth very little unless the data can help a business understand their customers as people.
Data enrichment is key to create a human-like understanding or each person, which includes analysing the data in unison to recognise and visualise a customer’s behavioural patterns, genuine interests and the affinities hidden within.
Until then, it’s nothing but noise.
Revealing what really matters to a customer and cascading this insight across the business can then have a profound effect on a telco’s success. For example:
- Improved high-level strategy and decision-making for everyone across the business.
- Marketers and advertisers can reach unique customer groups with tailored content, effectively turning communication from “spam” to relevant information and improved engagement.
- Sales and customer service teams can ensure every customer touchpoint is truly personal, enhancing their service when one-on-one with a customer, whether at the call centre or in-store.
- Innovation and commercial teams can monetise this customer insight externally, creating an extensive audience network with incredibly rich and detailed profiles.
It sounds ideal, but how can you make this raw customer data meaningful, or transform it into valuable insight?
It requires complex data enrichment technology, which is where many in-house solutions that telcos build, and attempt to manage, often fail.
For example, it’s useful to know that a customer (let’s call her Sally) visited a certain fashion website and called a particular theatre’s box office. This is what the basic data tells us.
From here we could presume that Sally’s pattern of behaviour shows she’s in the market for a new dress and loves the theatre.
However, unless we understand the bigger picture, we could be totally wrong.
Sally might have been buying a dress under duress for a one-off event or booking tickets as a gift, for example.
Presumptions based on past activity can give us some idea as to what she will do tomorrow, but we still need a complete profile enriched with context and meaning before we can predict future behaviour effectively.
This is the kind of insight – the acknowledgement of Sally’s wider interests – that is needed to successfully deliver moments of relevance, whether it’s communicating a compelling new offer or retaining Sally as a customer.
Historical actions are of course valuable, but, when profiling throws a wider net and looks at the person as an individual with likes, loves and peeves that change over time, it adds an invaluable new dimension of intelligence.
Artificial intelligence and machine learning specialists have focused their entire business on achieving this – and spent years perfecting it.
Solutions are now available that offer this level of enriched customer insight, visualised in an easy-to-use customer analytics tool for everyone in the company (not just the data and analytics teams).
These enrichment solutions can plug into existing tools to help build strategy and improve customer acquisition, retention and ARPU, covering off the entire telco wishlist in one swoop.
Despite this, some telcos are still slowly stitching together their own bespoke customer data solutions, buying an analytics tool from one source, storing data in another, and bringing in consultants from elsewhere spending months or longer waiting for the magic to happen.
Others recognise that their customer data is too important and too valuable not to take advantage of these proven solutions sooner.
Telcos and similar businesses that have already taken the crucial step to seeking enriched customer insight from their wealth of data have seen significantly faster growth across multiple business areas than ever before.
For those remaining, the need is becoming increasingly urgent as they risk falling far behind their competitors.