At the start of this week, Developing Telecoms looked at the importance of real-time monitoring, with a focus on customer retention and roaming. As we continue to explore the subject, we look at how targeted advertising relies on the accurate customer profile that real-time monitoring can create. In addition, a closely-monitored network can drive down the SIM-swapping endemic to emerging markets.
It’s no longer enough to send a campaign to a subscriber. Throughout an individual customer life cycle, an operator needs to continuously engage with its subscribers. The challenge for major operators – particularly in emerging markets – is that they have millions of subscribers who all have their own agenda. With ever more complex strategies, it’s very difficult to know how to treat these subscribers on an ongoing basis, let alone execute on these plans.
Big Data Analysis is the starting point. This involves connecting to all the data sources that exist within the operator and some that exist outside, such as social media. Consuming these events in real time allows for analysis of specific subscribers to understand their marketing profile, which changes throughout the day – SIM swapping is one example of this.
It’s important for operators to identify trends such as these, as they can then attempt to counter them by encouraging more customer usage on their networks. Having a broad marketing profile for each subscriber is advantageous. It needs to contain as much information as possible, whether this is static – such as the device they use – or dynamic behavioural information concerning the way they have responded to campaigns. Once this profile exists for each subscriber, the operator is able to match their strategy.
Until relatively recently in emerging markets, segmentation came down to whether a subscriber was prepaid or postpaid – and according to Udi Ziv, CEO of customer lifecycle management specialist Pontis, this is no longer enough. “At the end of the day, it has to be a segment of one”, he says. “Addressing each subscriber separately is ultimately the only way to avoid losing customers. Offers must therefore be tailored to individuals and fulfilled.”
Francois DeRepentigny, of big data analytics firm Guavus, agrees with this assessment. “It’s no longer enough to base customer campaigns on broad criteria – profiles have to be meticulously constructed and particular to each individual”, he says. “Timeliness and relevance of message are of great importance. The ability to respond to customers quickly, to be proactive at the right time, has always been key to customer retention and this is only accentuated in markets where prepaid is the norm.”
Without continuous interaction with the subscriber, campaigns will not be effective – particularly in emerging markets, where SIM-swapping is common and customer loyalty not as strong. Continuous and contextual marketing are essential for establishing consumer habits, which can then be used as the basis for a value proposition to keep the customer using the network.
Real-time monitoring of all the events taking place within the network – calls, text messages, USSD checks etc – allows operators to recognise behaviour patterns in customers and respond at an appropriate time. As Ziv notes: “If you’re the first person to reach your customer with a good deal, the odds are they’ll accept and this means they stay using the network for longer.”
DeRepentigny adds: “Understanding the patterns is crucial for a provider – encouraging users to top up at the right time may see them using your network rather than a rival’s. A lot of marketing power is spent on determining when to make an offer, and to whom.”
If for example a subscriber drops off an operator’s network at a similar time each day, it can be inferred that they are swapping SIMs in order to use a different network. While obviously it’s impossible to establish which rival network they are using, the user can be targeted with timely promotions that encourage them not to switch SIMs.
Some operators are still basing their responses on data which is days old, notes Ziv – this is simply not enough in the dynamic prepaid market. Real-time monitoring allows operators to present the right offer at exactly the right moment to the right individual.
The challenge is that network events happen in microseconds. Operators need to be able to garner the insight and then respond, and the quickest way to do so is to automate the process. This extremely small response window necessitates a better view in terms of segmentation. According to Oracle’s Gordon Rawling, one way of achieving this is through built-in analytics, as these allow the network to essentially guide itself in terms of promotions and offers once it has established what each user’s experience should be.
“While there isn’t a perfect definition of customer experience management, we all know when it doesn’t work, and it typically falls apart not because of the pieces, but the way the pieces don’t work together”, notes Rawling. “Business transactions need to be coherent to be efficient.”
Driving consistency and coherency is key – intelligence and analytics can lead to the ultimate ‘segmentation of one’, but this is all for nothing if the operator fails to deliver the service in the way they intended. The insight is important, but so is the execution; whether it’s a low-ARPU or high-ARPU market, the expectation is still the same.
“Customer retention is a core reason why service providers are putting in more effort”, adds Rawling. “There is a rich stream of value that can be garnered from intelligence in the network - operators are using customer information to optimise customer experience more effectively.”
Indeed, customer information represents a significant revenue source for operators – by selling it to third parties, they are essentially optimising data that previously went unused. For example, knowing which websites a customer has viewed might be of significant interest to a brand selling similar products to the site – and while this information has little value to the operator itself, third parties are willing to pay substantial amounts for it.
DeRepentigny notes that not all consumers are happy to have their data sold to other firms, but adds that this can be assuaged by real-time analysis of their usage data. By tailoring services to be more relevant to them as individuals, these customers will be less resentful that their information is being sold.
In much of Europe – among other developed markets – there are a lot of restrictions in place regarding the transparency of data collection. In Asia, this is not such a concern; markets such as Indonesia and Thailand allow for the collection and use of data without informing subscribers. DeRepentigny notes that subscribers are largely unconcerned by this as they already receive a vast amount of promotional, untargeted SMS advertising – there is an acceptance of advertising, and better targeting is considered a benefit.
Relevance is crucial for driving adoption – or indeed acceptance – of this kind of data usage among customers. If there’s no value, these campaigns and services will fall by the wayside – advertisers won’t want to use them and consumers will not sign up for them. Ultimately, they are customer-driven – which incentivises operators to find ways of providing benefits to their subscribers using real-time monitoring.