Tony Poulos Tony Poulos Market Strategist - TM Forum

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Dumping the Dudders (Big Data's Big Benefit)

  • Everybody seems to be talking up ‘Big Data’ and real-time analytics to improve the customer experience but no one is selling an even bigger benefit – dumping the customers you don’t want (the dudders)!

    Yes, you heard right. As a CSP, not only will you be able to see which customers are worth keeping, you should also have a clear indication of those that are simply not worth giving the time of day to. Extreme as it may sound, the cost savings could be enormous and your customer care, credit collection and save teams could be better employed looking after the good guys that actually make you money.

     

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    Think about it. Dissecting the data to collate how many calls a customer makes to your call center, how timely they pay their bills, how profitable they are, what they say on social networks about you, whether their net promoter score is positive or negative and whether they generate hidden revenues, like high terminating call rates, can easily point out the duds.

     

    Why would any self-respecting CSP want to keep customers that cost money in the long run? Why subsidize them instead of rewarding the good customers? Of course, axing them also brings the fear of retaliation or bad press but it may actually have the opposite effect. Just imagine you send out service termination notices to customers you no longer want with a simple yet polite reason for not wanting them and they, in turn, hit the social networks and press.

    BOOM - a massive marketing opportunity presents itself! The rest of your customers, when hearing that you are going to use the savings to give them a better service, will be chuffed. For those rejected, who will believe their story that the evil CSP is treating them badly? Your good customers will be in favor of their removal because they will almost certainly know someone just like that themselves – always whining about service, prices, coverage, the weather, etc.

    Other industries have already set the precedent. Banks don’t lend money to people that don’t pay their debts or have bad credit ratings. Airlines don’t have to carry people that are drunk, obnoxious or rude to their staff. Restaurants can demand dress codes, office buildings can insist on ID before allowing entry, insurance companies can reject high-risk individuals – the list goes on.

    If this sounds too radical then why not have different grades of service catering to the ‘undesirables.’ For customers on low value pre-paid tariffs the addition of a ‘no customer service under any circumstances’ contract term is a good start. For post-paid customers, a daily interest fee charged (just like credit card companies) for any overdue amounts. These people actually cost you money so why aren’t you putting your foot down?

    The best part of the selective dumping of lousy customers is that will end up with your competitor. Let them have all of them. You will definitely benefit in the long run. Better still, why not recommend your least favorite competitor to the departing dudders?

    Tony Poulos
    About Tony Poulos Tony Poulos works as Market Strategist at TM Forum
    More information : www.tmforum.org

Comments

3 comments
  • Steve Cotton
    Steve Cotton Tony:

    Good point. Makes me wonder if there will ever be a Ryan Air equivalent that makes hay on the most basic of services with the least lucrative of customers.

    All the best,

    Steve
    18 June 2012
  • Gadi Solotorevsky
    Gadi Solotorevsky Hi Tony,

    I agree with your rationale. I want to point out that most/all of the strategy you recommend could be implemented in the pre big-data era. I think that the two main challenges are not the data manipulation power, but being able to build th...  more
    19 June 2012
  • Jagadish Baddukonda
    Jagadish Baddukonda Tony:
    We all agree that sound analytics provides a good competitive advantage to a CSP. However, the uptake has been slow due to 2 factors.
    - Confusion in the CIO office as to the actual objective of the Analytics / Data Management exercise
    -...  more
    19 June 2012