Nokia touts predictive tool to enhance telco marketing
By Edwin Yapp July 9, 2015
- Marketers find it difficult to design campaigns without granular intelligence
- Predictive marketing tool can solve this, sidestep 'silo' problem
MARKETING organisations within telco operators are struggling to digest the vast amount of customer data they possess, and as a result, haven’t been able to benefit from the first-mover advantage this information could potentially give them, according to Nokia Networks.
The Helsinki, Finland-based telco vendor said that this is one of the main stumbling blocks that many telco operators face, and it has developed a software solution that can help.
Known as Nokia Predictive Marketing, the solution is actually an amalgamation of two Nokia product: Its Customer Experience Management (CEM) on-demand tool, and its Mobile Marketing Suite.
First introduced this year at the Mobile World Congress, Nokia said its Predictive Marketing tool can give operators – specifically their marketing departments – a complete picture of their customers’ activities, and turn that information into actionable intelligence that can help predict their future behaviour.
This will help operators target the right subscribers with the right message or marketing campaigns, the vendor claimed.
Harald Preiss (pic), head of South-East Asia for Nokia Networks, said a typical mobile operator collects huge amount of information from the network.
This information is first and foremost used to troubleshoot the network and to proactively solve mainly technical issues that impact subscribers.
Meanwhile, the same operator’s marketing organisation is also communicating with customers, creating campaigns and promotions along the way, he said.
Preiss argued that the challenge is that marketing cannot easily utilise network insights for marketing and sales purposes today, due to a number of factors.
“These factors include the fact that marketing, operations, IT, networks, and customer care are all ‘siloed’ in nature – in processes as well as in the tools they use,” he said.
“Marketing is therefore missing insights as to what is relevant,” he added.
Noting that it could take weeks of manual work for marketing to acquire network/ service data by customer segments and create targeted marketing campaigns, Preiss said campaign creation and personalised communications can be slow and difficult to run.
Another challenge is that it is difficult to monitor these campaigns, he said.
“This results in lost opportunities [for the operator] as only a limited number of campaigns can be run simultaneously,” he argued.
“Also, the [campaign] messages received by the customers may be too late, while operators cannot react soon enough to communicate or compensate unhappy customers,” he added.
Preiss claimed that operators using the Nokia Predictive Marketing tool would be able to put together intelligent strategies for their campaigns in a much shorter time.
Asked how different Nokia’s solution from the competition, Preiss said its solution is based upon two already proven products.
“Although major analytics vendors talk about similar abilities and provide solutions for marketing use cases, they generally lack a specific marketing analytics platform with integrated customer experience insights and prediction capabilities,” he declared.
Preiss said Nokia’s Mobile Marketing Suite has a data model driven by dynamic customer segmentation that allows every action to be recorded, and for the company using it to create a more personalised experience for their users.
“We believe we are the only telco vendor to use predictive analysis based on machine learning in its services offering,” he said.
Quizzed as to whether there are customers in South-East Asia that are already using its Predictive Marketing solution, Preiss declined to comment, only noting that the solution is relatively new and has only recently been announced.
However, he said customers such as T-Mobile USA have successfully deployed Nokia’s Mobile Marketing Suite tool to integrate all of their customer relationship management (CRM) and related systems into a single platform.
According to a case study, Preiss said T-Mobile claimed to have gained the ability to reach 100% of its customers, and to do so intelligently, through the channel they prefer, at the time of day they like, and with the information and offers they are most likely to value.
“Our solution collects insights from customer devices, and utilises advanced algorithms to predict customer behaviour,” he declared.
“With this easy-to-use tool, targeted campaigns can be created within an hour. They can also be run automatically based on rules that have been created earlier.”
For more on T-Mobile’s case study, click here.
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