Using Predictive Analytics to Put a Spin on Old Marketing Campaigns

Posted: June 19th, 2013 | Author: | Filed under: Industry Insights, Telecom Trends | Tags: , , , , , , , | Comments Off on Using Predictive Analytics to Put a Spin on Old Marketing Campaigns

Three years ago, I was writing my first blog post about how I had received a package from Formula One racer Kimi Räikkönen, the coolest guy in the universe. In Finland, as part of our school traditions, every first grader gets his or her first mobile phone at the age of seven. That is when our award-winning school system begins to educate our offspring in order to meet OECD and Pisa test requirements. The battle for these new mobile subscriptions is fierce, with communications service providers (CSPs) offering a wide range of options to parents and their kids.

This week, the same package arrived for the next class of first-graders – only this time, Angry Birds had replaced Mr. Räikkönen as the mascot. Finnish mobile operator DNA Finland sent a prepaid SIM card to every Finnish mom (including me) who had a child that was born in 2006 and entering the first grade. Three years ago, I thought that this campaign was extremely clever. Now, though, I’m wondering if DNA Finland could have learned something during the past three years. Sure, the mascot may have changed, but the campaign is largely the same. With new tools like predictive analytics available to CSPs, it seems like the marketing could become much more sophisticated.

DNA Finland knows that I am not their customer and the same applies to other household members. As Comptel’s recent global consumer study showed, having friends and family members who were using the same operator was the third most important factor (41%) for consumers when choosing a CSP. Does DNA Finland know that I didn’t choose them three years ago? Could this campaign have been better customised for mothers who aren’t already DNA Finland’s customers?

I have been waiting for Elisa’s counter offer and I’m wondering if they are using analytics to discover that I am extremely likely to bring them new business by August. After all,  our family already has a wide selection of Elisa’s offerings – four mobile subscriptions and one broadband (ADSL) connection. One mobile subscription is for the enterprise customer segment, our broadband connection is in the corporate segment and the rest of our SIM cards are under the consumer customer brand Saunalahti.

I can’t help but wonder if all that information is scattered across various silos and systems. That could make it difficult to apply analytics to all that data and leverage it for new marketing campaigns. Ulla Koivukoski, Comptel’s senior vice president of the analytics business unit, recently wrote  about the distinct silos in CSPs and how business units aren’t always looking to solve the same problems. Customer Experience is the issue that bridges the divide between all the competing business interests. And, while receiving an Angry Birds-themed package is nice, I would have remembered something that was personalised a lot more.

With current targeting methods marketers typically end up either with target groups that are too defined and small – it does not make sense to campaign or the campaign scope is too generic and therefore likelihood of inaccuracy increases, as the case in the angry birds campaign. Comptel Social Links can change the mind-set in marketing by combining the marketers’ expertise of selected target group with machine learning letting the algorithms find the customers most similar to the obvious customers. Predictive modelling results will be available for the marketing team instantly, resulting in more accurate hit rates for campaigns, higher customer satisfaction and finding optimal users for the product or service marketed.

CSPs want to make sure that customer service is as good as possible. If you’ve delivered a great customer experience, your efforts are turned into new business opportunities. The first step, though, is to find out just how to use the data you already have to deliver that customer experience. Maybe the next group of first graders will get packages that are a little more customised.


The Benefits of Social Network Analytics for Marketing

Posted: August 14th, 2012 | Author: | Filed under: Industry Insights | Tags: , , , , , , , , , , , | Comments Off on The Benefits of Social Network Analytics for Marketing

Social network analytics (SNA) is becoming increasingly popular as communications service providers (CSPs) look to better understand their customers and secure a competitive edge in the market. As part of an advanced analytics approach, SNA enables CSPs to dive into the billions of daily transactions on their networks and utilise the calling patterns to identify influencers and better segment their subscribers – and ultimately realise more value.

For instance, call detail records provide CSPs with a unique insight into social interactions through the daily communication of their subscribers. This network may be even more important for CPSs than most online social networks, for example, which are just snapshots of a person’s interactions, many of which may not be very relevant, especially with regards to the activities of CSPs.

However, SNA alone is not the ultimate end-all solution and is, instead, one very valuable aspect of the larger scope of analytics. And when combined with predictive analytics, SNA truly offers a distinct advantage for CSPs. For instance, they can use SNA to power their predictive capabilities and generate insight regarding data that is otherwise unavailable on the single subscriber level. On top of this, SNA and predictive analytics can help CSPs benefit from the interactions between subscribers, help with overall customer experience management and automate operational actions to increase productivity. And let’s not forget, perhaps the best known application of SNA, viral marketing – an approach that remains one of the strongest, most effective marketing techniques. But again, it’s crucial to take into account that understanding the social network alone is not enough. Rather, when combined with the right product, predictive analytics powered by SNA can really make a difference.

Take, for instance, a teenager who texts frequently. If he or she receives an appealing SMS rate reduction that’s just right for them – perhaps one that predictive models have indicated would be suitable – this subscriber will be more likely to spread the word to those in his or her network, causing a positive ripple effect. As a result, many of these connections may pursue that same SMS rate, providing an increase in revenue for the CSP.

Ultimately, recommendations from family and friends can be far more effective than traditional advertising. In this way, combining predictive analytics and SNA can play a key role in any CSP’s arsenal. And of course, a well-executed SNA strategy balances providing personalised offers without infringing on subscriber privacy.

If you’d like to read more about combining predictive analytics and SNA— and taking this even one step further to understand and act upon the context of each interaction — download our recent whitepaper with Heavy Reading on Contextual Intelligence. What are your thoughts on SNA? Is it of value? Are there actual network influencers whose recommendation you follow regardless of the topic? Or would you say you’re more swayed by having CSPs make the right offer, and it holds more weight when the offer is recommended by those whose opinion you trust in the context of what is being offered?