While the algorithms utilized in artificial intelligence are widely available to telcos, the critical challenge, according to Niilo Fredrikson, the executive vice president of Comptel's Intelligent Data Business Unit, is to apply these algorithms shrewdly.
Fredrikson told Telco Transformation that the core of the task is to develop platforms that use these powerful AI and machine learning capabilities to more intelligently address prospects at the right time and with a unique and personalized message based on that person's known tendencies and prior behavior. Late last year, Comptel introduced Fastermind, an AI-based platform aimed at telcos that can be utilized to improve customer engagement.
Telco Transformation: What is Fastermind and where does it fit into Comptel's overall organization?
Niilo Fredrikson: Comptel Corp. (Nasdaq, Helsinki: CTL1V)'s business is structured into two business units. The first is called service orchestration. The second, which I lead, is called intelligent data. Our focus is the digital customer journey.
This means, essentially, enabling telecom operators to create smooth contextual and intelligent experiences for their end customers across all the touch points, including the cross-sell and upsell offers and customer care inbound and outbound touchpoints. Through these, telcos will be able to increase revenues, increase customers' satisfaction, and also decrease time to market.
We make it happen is with three product portfolios. The first one is called Data Refinery, which is a data integration and complex event processing platform. The second product is called Monetizer, which is an agile offer creation tool that sits on top of policy and charts and functionality enabling the alteration and deployment of new data plans in minutes.
The third product is Fastermind, which includes two core functionalities. It's a real-time decisioning logic builder and a rules engine. The second part is the AI part, which is essentially a set of deep analytics and machine learning capabilities.
TT: What is the first element?
NF: There's something we call Real-Time Decisioning or RTD. That essentially is a business logic builder. For example, a product manager or a marketing director at a mobile operator can use this user interface to in a graphical way to build different customer engagement logics, which are then automated and which leverage the second piece, which are the analytics and machine learning capabilities.
TT: Can you provide an example of how Fastermind works?
NF: Let's look at the subset of those customers who either through their phone or through a computer added an iPhone into their shopping basket but have not completed the purchase. Then let's add a location trigger, which says that, okay, a customer, who fulfills these two criteria comes close to our retail location. Let's send him a notification in real time, prompting the customer to visit the retail location and say, "Hey, we have the phone that you were looking at in stock. Why don't you come by and we can show it to you?"
Then there is a fourth piece, which is now related to a deep analytics part. Let's also create a special discounted offer for this particular situation or customer based on an analytic score, which is an estimate of that customer's likelihood to react to different size discounts and make a purchase decision based on that.
TT: This sounds like it can be done with a sophisticated rules-based engine. What is the AI element?
NF: In this specific example, the true AI part of it is the machine learning aspect of determining the customer's likelihood to buy based on a discount offer. It is about the analytics score, which tells what the customer's propensity to buy is based on a discount.
Then, there is a feedback loop based on machine learning where we look at all the purchases and new data coming in and constantly change the algorithm so that it learns by itself and becomes better and better. The score is individual for each user. The algorithm used is a self-learning neural network, which is by nature a machine learning algorithm. It adjusts the results and outcomes based on data coming in over time.
Next page: Two approaches to AI: number crunching and 'thinking'