Posted by Ajay Kelkar on Tue, Oct 13, 2009
The good news, for marketers, is that data mining really can make a difference to most bottom lines. The bad news is that, despite what data mining can do, it is so often used so poorly that it is virtually useless. Companies are today storing huge amounts of data. Companies in the 'Petabyte Power Players' club include eBay Inc., with 5 petabytes of data, Wal-Mart Stores Inc., which has 2.5 petabytes, Bank of America Corp., which is storing 1.5 petabytes, Dell Inc., which has a 1PB data warehouse In many cases, the data is a big part of the problem. Even in the most reputable companies, data is often "dirty,"--out of date or otherwise irrelevant. Most commercially available data mining packages lack the flexibility and functionality that real world marketers need. The problem with "data quality" is ownership. No one seems to own this critical asset! Without doubt , the line functions have to own "data quality". Data quality can only be impacted substantially "at source"-either a salesperson fills up inaccurate information for a customer while he wildly chases his target or an operational group incorrectly data enters a customer record!One of the most frequent and most difficult causes of data quality is culture. If people do not think that data quality is important, it isn't.James Standen makes this interesting point;Data quality starts on the ground. The further from the ground, and the deeper into various operational systems, ETL jobs, staging tables, data warehouses or data marts we try to fix the problem, the harder it will be.http://blog.cequitysolutions.com/ The Numerical Algorithms Group (NAG), an organization that develops software to solve complex mathematical problems, has three suggestions. One, try hiring a mathematician who is a data-mining expert to guide your efforts. Two, consider developing data mining applications in-house using fully documented components (algorithms) from a reliable library. And finally, don't give up. When data mining works, it is well worth the effort.See what Rob Meyer has to say about ‘A Better Way to Mine Data’. http://www.nag.co.uk/IndustryArticles/ABetterWaytoMineData.pdf
Posted by Ajay Kelkar on Thu, Jun 18, 2009
Customers are using your services through multiple channels. Customer's access their bank through either the branch or Internet banking or other channels such as ATMs and mobile banking. Multi channel behavior however needs to be intelligently decoded. Mc Kinsey research shows that Multichannel customers spend on average 20 to 30% more than single channel users. More than 80 percent of a broad cross-section of U.S. retailers now report that they sell merchandise through multiple channels. Currently, customer data are rarely analyzed to understand how individual customers behave across channels. This, however, seems to be the key to understanding the intricacies of how the channels work together. Have a look at this interesting Mc Kinsey research- Steering customers to lower cost channels.pdf
Also it is no point doing the analytics and then not taking action! Multi channel behavior is a huge opportunity for a marketer if you are able to consistently use each interaction to market better! Intelligent use of technology to improve the customer's multi channel experience can be a huge differentiator! Especially in growth markets such as India a lot of companies are at an early stage of customer acquisition. Relevant technology brought in early can make a huge difference.
James Taylor has this interesting take on how a bank can make your multi channel experience a powerful competitive advantage.
Here is what he says
"So, what if your bank...
- always identified you when you put your card in the ATM, called the call center, handed over a check at the teller
- remembered your preferences
- remembered your regular activities and prioritized them
- accurately predicted your likely behavior/needs
- applied constraints and circumstances (ATM wait time, call center wait time, teller v personal banker) to its approach
- used the information you gave them, no matter how you gave it to them
and so on...
How might that look?" Check out more at http://www.edmblog.com/weblog/2006/09/using_decisioni.html
Posted by Ajay Kelkar on Sun, Jun 14, 2009
Last week, Cequity was speaking at an event hosted by the Retailers Association of India(RAI) and the topic was really about how Retailers can make Customer experience their true diffrentiator!
The interesting thing in Retail is that eventually ,competitive advantage in location,merchandize assortments & price can be replicated by competition ,but Customer experience can be a unique diffrentiator. The difficult thing about this is that Retail brands have so many touch points with customers and how do you make each of these interactions "memorable".
Many organizations,especially in growth markets & industries are already dangerously "out of synch" from their customers. One of the indicators of this is this Bain’s research
that found 80% of companies believed they were delivering a superior
customer experience while only 8% of their customers thought they were receiving
a superior experience.
I believe that the key lies in not making the "customer experience" the accountability for any one function but rather making it a key company competency across function. Bruce Temkin of Forrester has this interesting perspective "Treat customer experience as a competence, not a function.
Delivering great customer experiences isn’t something that a small
group of people can do on their own — everyone in the company needs to
be fully engaged in the effort. It all starts at the top; the CEO and
his executive team need to be fully engaged in the effort. To keep a
companywide focus on customers, companies need a systematic and
continuous approach for incorporating customer insights into all of
their efforts. That’s why we recommend building a voice-of-the-customer
program".
In the last 12 months Customer experience management (CEM) has started to get more profile but it is still just a good idea emerging into an area of marketing thought currently dominated by CRM. CEM is currently a poor cousin to CRM. If it is to grow up and become a powerful business tool it must move out of marketing and directly link itself to business outcomes. See what Adam Ramshaw has to say about ‘Will Customer Experience Management grow up big and strong like its rich cousin CRM?
http://crmguru.custhelp.com/cgi-bin/crmguru.cfg/php/enduser/std_adp.php?p_faqid=1638
Posted by Ajay Kelkar on Fri, May 08, 2009
The complaining customer - we just can’t stand them! Well, most of us can’t stand them. The reality is that business organizations should love them. Shep Hyken comments that "A complaining customer tells you where you can improve. They actually come forward and show us where we make mistakes. But, most of the time, people hate to hear the complaints. First, a few facts you should know about people who complain. Most of the time, when people have a complaint, they complain to everyone else rather than the person or people who caused the complaint. If you resolve your customers’ complaints, you will keep them most of the time. But first you have to know there is a complaint. So, how can we find those complainers? Well, most likely customers won’t tell us, so, we have to ask them. It is that simple. Call them up or ask them in person. Actively solicit feedback to find out what they are thinking."
And most criticaly use Customer behaviour data to spot Customer service failures as they occur. Customers are constantly leaving behind a data footprint of "failed brand promises". Direct data analytics to spot incidents of customer promises "not met". The crux of " Analytical marketing" is using data to drive an improved customer experience. Imagine if a bank were to call you up and say " I am sorry sir ,we are one day behind schedule on your cheque book request,please accept our apologies and your cheque book will be with you tomorrow morning". Or better still build predictive models to find customers where "service levels are likely to slip" and then proactively monitor that customer's transactions to create a moment of delight.
And when you find a problem or complaint, resolve it on the spot. No company is perfect. So find out what those imperfections might be. And, when you hear about a problem, fix it. And make sure you give that customer a reason to come back so you can do it right the next time. Take that moment of misery and turn it into a MOMENT OF MAGIC.See what Shep Hyken has to say about ‘The Complaining Customer’http://www.hyken.com/Article_11.html
Posted by S Swaminathan on Fri, Feb 06, 2009
Chris Anderson has written a great article in Wired on the data deluge and how it poses new challenges to the companies. He writes that the petabyte age that we live in information is not a matter of simple three- and four-dimensional taxonomy and order but of dimensionally agnostic statistics. For companies, that have or gather loads and loads of data, the implications are about how can they quickly sift thro' this massive volumes of data and the successful ones will be the ones who can track and measure this with unprecedented precision and scale. Take a look:
Speaking at the O'Reilly Emerging Technology Conference this past March, Peter Norvig, Google's research director, offered an update to George Box's maxim: "All models are wrong, and increasingly you can succeed without them."
This is a world where massive amounts of data and applied mathematics replace every other tool that might be brought to bear. Out with every theory of human behavior, from linguistics to sociology. Forget taxonomy, ontology, and psychology. Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves.
The big target here isn't advertising, though. It's science. The scientific method is built around testable hypotheses. These models, for the most part, are systems visualized in the minds of scientists. The models are then tested, and experiments confirm or falsify theoretical models of how the world works. This is the way science has worked for hundreds of years.
Scientists are trained to recognize that correlation is not causation, that no conclusions should be drawn simply on the basis of correlation between X and Y (it could just be a coincidence). Instead, you must understand the underlying mechanisms that connect the two. Once you have a model, you can connect the data sets with confidence. Data without a model is just noise.
But faced with massive data, this approach to science - hypothesize, model, test - is becoming obsolete. Consider physics: Newtonian models were crude approximations of the truth (wrong at the atomic level, but still useful). A hundred years ago, statistically based quantum mechanics offered a better picture - but quantum mechanics is yet another model, and as such it, too, is flawed, no doubt a caricature of a more complex underlying reality. The reason physics has drifted into theoretical speculation about n-dimensional grand unified models over the past few decades (the "beautiful story" phase of a discipline starved of data) is that we don't know how to run the experiments that would falsify the hypotheses - the energies are too high, the accelerators too expensive, and so on.
Read more on understanding data
Posted by S Swaminathan on Sun, Feb 01, 2009
Here's an interesting trend from emarketer on what to expect in the next couple of years on content and data of what & how customers will watch TV and consume entertainment which will become available for analytics & customer centric marketing.
"At eMarketer, we believe TV viewers will watch more, not less, TV content in the future," says Ben Macklin, senior analyst at eMarketer and author of the new report, TV Trends: Consumers Demand Control. "But they will be accessing and viewing it in different ways from the past."
eMarketer estimates that by 2012 nearly 25% of all TV content watched each day will be time-shifted, on-demand, on the Web or on a mobile device.
"Video-on-demand, digital video recorders, the broadband Web and 3G mobile phones are giving consumers new ways to access and watch TV," says Mr. Macklin. This does not spell the end of the traditional live TV broadcast or the traditional 30-second ad break, but TV advertising will need to evolve if it is to keep pace with consumer usage.
"Traditional TV broadcasters and advertisers have little time to wait to reinvent themselves and their organizations to take advantage of the interactive, on-demand and mobile video future," says Mr. Macklin.
Posted by S Swaminathan on Fri, Jan 30, 2009
Here's an interesting article from 1:1 Media on how even a well established company like Sony wants to embrace customer-centricity:
At last week's Conference Board Customer Loyalty conference, Sony Electronics Senior Vice President of Service Platfom Dan Wiersma asked attendees how many of them owned Sony devices. Every hand in the room went up.
So why would a company like Sony, which has so many customers, look at customer-focused initiatives to drive loyalty programmes? "Customer loyalty is the pathway to long-term sustainable growth," he said. Even a company as successful as Sony can't rest on its laurels as competitors flood the marketplace. "Technology is still important, but the customer experience is critical."
Sony discovered that customers have very high expectations of quality across the customer experience, from the products themselves to the packaging. "In some cases the packaging inside the box was just a pile of papers," Wiersma said. "Customers expected something more sophisticated and organized from Sony."
In another example, Sony discovered that customers shopping in a Sony Style store consider it a high-end experience. They wanted a nice box and bag for their purchases, so they could walk around showing off their purchase [à la the very recognizable Tiffany's blue bag.] As a result, in November the company redesigned its Vaio computer box and reorganized its packaging. As an added touch, each box now contains a thank-you card from Vaio's senior general manager, containing his direct phone number and email address.
These are just some of the first steps in Sony's loyalty journey, Wiersma said. While the Vaio product group has been very aggressive with its loyalty programme strategy, some other groups are a little slower to take action. In addition, Sony plans to start working with retailers to identify and interact with the majority of Sony consumers who remain anonymous.
Wiersma hopes to keep internal momentum going with assigned "loyalty leads" for each business unit to help support the loyalty programme strategy. Sony has also set up an internal website called Customer Experience Excellence, where every employee can view loyalty data such as customer verbatim, survey results, and business unit action plans. "It gives employees the opportunity to leverage their capabilities and compare themselves to other business units," Wiersma said.
Posted by S Swaminathan on Sun, Jan 25, 2009
Out-of-stock, poorly timed inventory levels and other lost sales opportunities present a problem for retailers.
They frustrate consumers and cost retailers and consumer product companies.
A growing group of companies are targeting this problem. Companies can create a highly sophisticated picture of what's happening at every step of a product's journey to the consumer purchase by harnessing the store-level sales data that retailers make available to suppliers and incorporating analysis and other relevant information like weather patterns.
The promise of demand data analytics - the catch-all phrase for such services - is that a better understanding of how, why and when people buy coupled with more knowledge of the supply chain and store-level execution will help stores stay stocked with the right stuff at the right time.
TrueDemand is one of the companies hoping to capitalize on the situation and has established a Bentonville office to better serve its growing Wal-Mart supplier clientele.
The company created software that takes Retail Link data, the sales data that Wal-Mart Stores Inc. provides to its suppliers, and analyzes it on a daily basis. Then, it creates company-specific, daily reports that predict out-of-stocks and prioritize actions at the store level to help prevent them.
Shiloh Software has become a market leader of data mining tools. It takes information from Retail Link and integrates data from a number of other syndicated data providers like NPD Group Inc. and ACNielsen, and other information like weather forecasts, U.S. Census Bureau data and store-level traits like whether it's by a university or in a largely Hispanic community.
Read more to find out how analytics play an important role in retail demand prediction.
Posted by S Swaminathan on Fri, Jan 23, 2009
Here's an interesting presentation of what will be the next phase of customer relationship management by Paul Greenberg:
[slideshare id=462481&doc=crm-state-of-the-market-2008-beyond-1213217988913940-9&w=425]
Posted by S Swaminathan on Tue, Jan 20, 2009
It's always easy to think about marketing metrics but very difficult to implement on the ground. Here's a great case study by US Bank presented at the recent ANA Marketing Conference last week: