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April 2013
Imagine how easy it is for an e-commerce firm to manage its customer experience.
When an Amazon sells a book, it’s a one-and-done deal. The book is shipped by a distributor and there’s a clear chain of custody. And if it’s a Kindle e-book, that was either received successfully or it wasn‘t. The transaction is neat and clean.
Now compare that to the monstrous complexity in the telecom customer experience:
Well our guest in this column, Anssi Tauriainen, and his company, Aito Technologies of Finland, are at the cutting edge of bending B/OSS data to the task of both analyzing the customer’s network experience and associating that with actions to improve it and drive greater revenue.
Dan Baker: Anssi, I understand your company kind of grew out of a university project. |
Anssi Tauriainen: Yes, Dan, I spent 10 years in different roles at Nokia Network. That’s where I really learned telco processes. They sent me on various assignments: worked a couple years in North America, some years in Germany and also many projects with Asian customers. So when I moved back to Finland in 2004 I took a break to get my Ph.D. and I decided to do my research on a topic that was a fresh idea at the time: customer experience management. Two and a half years later I was pleased that the telecom industry had adopted customer experience as a buzzword. So it was perfect timing in 2007 for me to found Aito and focus on customer experience analytics (CEA).
I’m sure that studying for your doctorate gave you plenty of good thinking time. What did you discover as the main weak point in the way telcos manage customers.? |
If I were to sum up the weakness in one word, it would be “silos” -- multiple dimensions of silos actually.
Now it’s easy to understand that various B/OSS systems often don‘t integrate well, but in CEA it’s bit more complicated because you are also trying to move the customer through various lifecycle stages.
At Aito, we think of the customer life cycle as divided into five distinct stages.
Now each of these stages has a different set of OSS and BSS system. We’ve found that in each phase at a typical operator there are five or more systems that are generally not integrated well with each other.
So the way to think of this is that you have silos within silos! And every time you move from one life cycle stage to another, you are typically moving the customer into different systems and often the data from the previous stage is lost. See the diagram below.
For example, in the Attract phase, you have campaign management systems. Later on you have provisioning, service assurance, and billing systems. CRM and Customer Care systems are critical in the grow phase, and finally there heavy use of BI and analytical solutions for the Retail or Churn phase.
So the secret to doing CEA right is to combine the relevant information that crosses the individual life cycle phases. And now I think you begin to see how hard it is to do this because if there are at least 5 B/OSS systems in each stage, that gives you 25 systems to integrate.
So, our CEA solution is kind of a plugin component that unifies the relevant customer traffic billing and product information from relevant sources to come up with analysis that covers the whole life cycle. In a typical scenario it is deployed on top of 3 individual critical silos or existing data sources such as probes, CRM systems, data warehouses, and billing systems. CEA collects all of the data it needs in real time and combines it to gain an understanding view of how customers are evolving through the life cycle. The number of connected silos can be higher but analysis can be formed on the basis of 3.
What are the consequences of not having this uniting layer that integrates the silos? |
Well, first and foremost, marketing decisions are often totally out of sync with what is actually happening in the network. Take customer lifetime value: telecoms still have no effective way to estimate the value and profitability of individual subscribers.
What happens is that any time you need to improve sales and marketing campaigns or optimize the network, you make a lot of assumptions based on partial data. That’s the problem we are trying to correct.
And we do that by measuring the variable costs of providing a service — termination fees, interconnect costs, and a traffic-analysis-based cost of the money being spent to serve customers. The only thing we don‘t estimate are the fixed CAPEX investments, but you can easily apply those figures on the top of what our solution delivers.
Besides the integration layer, what else is different about your approach? |
I think the unique part of our offering is the ability to combine commercial data with technical data, particularly merging the customer experience, quality of service or network management view with the revenue view.
The data we provide, for example, allows the operator to view customer experience and behavior at a segment or individual subscriber level. And this is especially useful when analyzing VIP or high-margin customers.
So, we can go back and pinpoint individual root causes and bottlenecks in the network that would enable the operator to improve the experience for those particular customers.
To accomplish this technically, we collect all the traffic from the network -- the CDRs, the XDRs, and also the data content that DPI collects. We then combine that with customer demographics, background data, segment information, and billing data. Altogether it provides a reliable value for the revenue each individual subscriber is generating in the network.
We also can rate and score individual subscribers automatically and feed these indicators to be used in 3rd party systems. We support over 100 scores and an example of that integration is the Aito-provided Customer Experience Index for use in Customer Care applications.
It sounds like a very comprehensive solution. |
It is comprehensive, but we’ve found that even when you put the right data and analytics in front of them, operators still have a hard time taking action from this information.
This is why a key aspect of our practice is to hone in on the needs of a single user group.
There are essentially six key user groups we serve. And as you can imagine, we sell our solution in modules so that the operator only has to buy the functionality it needs to solve its particular user case.
The main user groups are shown in the diagram below and here is what each group is basically looking for.
How about a case study? |
Well, a good one is the work we did at UCell in Uzbekistan. UCell was acquired by TeliaSonera in 2007 and now has a market share of 32%, reaching about 8 million subs. The company grew by targeting younger audiences with voice, data and mobile broadband services and running lots of marketing campaigns featuring low cost price plans.
UCell called us in to help in 2010, and our mission was to help them do real-time analysis of customer experiences and behaviour to improve its segmentation targeting of marketing and offers to the customer.
So we collected the traffic information, CRM data, and billing data and gave them an understanding of how their products and services are being used today. Then they used our solution to target their campaigns.
After the campaigns the team can monitor day to day usage and react immediately to changes in customer behaviour and campaign performance. Technical problems in the network can also be discovered, such as poor coverage, enabling network operations to quickly identify the root causes of the issue and rapidly and proactively fix them.
Thanks for the nice briefing, Anssi. |
Copyright 2013 Black Swan Telecom Journal