Recently I bought three pieces of furniture from House Full. They are a furniture retail chain with maybe over 5 outlets in and around Mumbai. They are probably the only chain currently present in Vasai area. Once I had selected and finalized the three furniture pieces, the attendants threw a surprise that the furniture come in a ready for assembly state and they will charge me Rs. 300 for sending over the carpenter to assemble the item. Since, I did not have much of an option (especially since my wife and daughter had selected the items), I reluctantly agreed to pay this amount.
Then started my travails. The delivery guys came over within two days and promptly dumped three cartons in the house. However, instead of a clothes dryer stand which I had ordered, they dumped a bean bag and left. I had instructed the outlet to send in the carpenter on a saturday. However, he arrived on Friday morning. The moment he arrived he started cribbing about how far the house is and the fact that he had to spend money on an auto-rickshaw to reach the house. He stated that HouseFull does not reimburse him the travel fare and he has to shell it out of his pocket.
He was pretty grumpy all the time. He assembled one of the furniture fine. For the next one, in his bad attitude he banged one of the panels to the wall. Thereby damaging both the wall and the panel. The panel had a chip off from one of the corner. He continued assembling the piece. Once done, he put the caps on the screws on one side and handed the rest of the caps to my wife and said to do it ourselves. Then he left abruptly still cribbing about the return fare he has to shell out.
I went to the retail outlet that weekend and complained against this behaviour of the carpenter, the damage caused to the furniture panel and the incomplete work with the screw caps. The attendant said that the carpenters are locals and the company has no control on them. He said he would take down the complaint and will have it attended to. Nothing happened after that. No phone calls ... no contact. They just replaced the bean bag with the clothes dryer stand after almost a week. The delivery person said he just delivers and is not concerned with any issues I had with the company.
Two weeks back, I walked in to the same HouseFull outlet looking to get a bookshelf. They had one which I liked. This time I told them that I will not pay for assembly and will do it myself. I said I will not pay the Rs. 300 they charge for assembly. The attendant said that I will still have to pay the delivery charges. He said the Rs. 300 includes delivery and assembly charges. Now this was not the same that was conveyed the first time. I was told delivery is free and Rs. 300 is for the assembly. I told him the same. Anyways, I asked how much is the delivery charge. He had no clue and told me that he is not sure about it. Next he changed his stance and told me that they will deliver but will not be responsible for any damage to the panels in-transit. I asked to see his manager. I told the manager that in this case what about the damage caused by the carpenter during assembly the first time. He again had no answer. He just took down my number and address. A carpenter came over to my place with no clue to what is expected out of him. I sent him back. That was it. No further interaction with HouseFull.
It is really surprising how companies outsource the customer contact activities. These are the interactions which create lasting impression and defines how the relationship will develop. If customer relationship is the heart of a company, it is like giving this heart in the hands of an outsider and expect him to pump it a the right interval.
At one of the B2C setup of a corporate house, I was studying the customer relationship process. I found a lot of problems with the call center. I raised this in my report to the operations manager. He said that he cannot do anything about it. The corporate house had decided to set up a call center and being of the same group, the company was forced to give its call center business to this setup. But while the call center was learning, the customers were leaving. It was a CRM harakiri.
Customers are the heart of any company. Any activity that has direct contact with the customer should be under complete control of the organization. Contracts and SLAs cannot bring in the customer ownership attitute. Companies must seriously rethink outsourcing their customer contact points. Its not a question of cheaper process with the vendor. A lost customer is much costly than the few rupees saved in servicing him with an outsourced vendor.
Monday, December 19, 2011
Monday, December 05, 2011
Have Data .. Will Mine
I recently recalled a very amusing episode. This occurred way in the past. I had spent the whole of the morning with a general insurance customer discussing claim analytics and claim prediction for automobile insurance. From there I rushed off to meet another client who operated in the life insurance space.
The client was busy with some worksheet data. I asked him what he was up to. He said he has received scores for a new model. I asked him which model is he building now and he told me it was claim prediction. Since I was with a general insurance customer, my mind was still oriented to the general insurance business. Instinctively, I asked him what his definition of claim was. He said with a smirk that claim is when the life assured dies. Then, it hit me that I am sitting in a life insurance business premises. We joked about the fact that we are actually trying to predict the death of a person. We laughed about what the output can be used for. One option was seeing that a person is predicted to die, the company can refuse to take his renewal policy and let it lapse. Imagine the call center interaction --- "Hello sir, since we see you are not likely to live over the next 18 months, we would like to terminate the life insurance policy. Thank you for being a good customer while you were alive."
I hinted that it was a pretty sadist model that he was building. Anyways, we got to the worksheet and I asked him who did this model. His outsourced analytics agency built this model. I asked him to show me which variable was most dominant in generating the claim score. I was not surprised to find that age was the dominant variable. It showed younger customers were less likely to die than older ones.
While the client understood that this was not the right approach, it was amusing that the analytics agency actually built a model for claim prediction. It was a true case of "since I have data, I will build some model". The agency did not question nor advise the client on the right approach to solve the business issue. The client wanted to arrive at expected expenses, including claim over the next couple of years.
In life insurance, the amount of data about the customer is very limited. Claims occur on termination of life (we are not discussing riders here). Length of life depends on quality of life, which in turn depends on various factors such as diet, lifestyle, etc. And not to mention homicides. Information which is not available in the life insurance database. Hence, the approach is to go macro or at a higher level. One should look at mortality of the target market and then draw a proportion of the policy base from the target base. This will give a good estimate of the number claims likely to come in. The analytics agency should have done a forecast of the deaths in a target location. They could have done this either (inside out) by taking the past experience of the life insurer and extrapolating it over the market for forecasting or (outside in) by taking the deaths registered in a target location and then adjusting the forecast for the profile of people buying policies with the insurer.
But instead, we had a typical mentality of a kid who when given a hammer thinks everything is a nail. Since there is data available, a model was built. On this topic, do you know "the salary of a product manager is inversely proportional to the unit price of the product." (findings from one of the models when I was a analytics infant).
The client was busy with some worksheet data. I asked him what he was up to. He said he has received scores for a new model. I asked him which model is he building now and he told me it was claim prediction. Since I was with a general insurance customer, my mind was still oriented to the general insurance business. Instinctively, I asked him what his definition of claim was. He said with a smirk that claim is when the life assured dies. Then, it hit me that I am sitting in a life insurance business premises. We joked about the fact that we are actually trying to predict the death of a person. We laughed about what the output can be used for. One option was seeing that a person is predicted to die, the company can refuse to take his renewal policy and let it lapse. Imagine the call center interaction --- "Hello sir, since we see you are not likely to live over the next 18 months, we would like to terminate the life insurance policy. Thank you for being a good customer while you were alive."
I hinted that it was a pretty sadist model that he was building. Anyways, we got to the worksheet and I asked him who did this model. His outsourced analytics agency built this model. I asked him to show me which variable was most dominant in generating the claim score. I was not surprised to find that age was the dominant variable. It showed younger customers were less likely to die than older ones.
While the client understood that this was not the right approach, it was amusing that the analytics agency actually built a model for claim prediction. It was a true case of "since I have data, I will build some model". The agency did not question nor advise the client on the right approach to solve the business issue. The client wanted to arrive at expected expenses, including claim over the next couple of years.
In life insurance, the amount of data about the customer is very limited. Claims occur on termination of life (we are not discussing riders here). Length of life depends on quality of life, which in turn depends on various factors such as diet, lifestyle, etc. And not to mention homicides. Information which is not available in the life insurance database. Hence, the approach is to go macro or at a higher level. One should look at mortality of the target market and then draw a proportion of the policy base from the target base. This will give a good estimate of the number claims likely to come in. The analytics agency should have done a forecast of the deaths in a target location. They could have done this either (inside out) by taking the past experience of the life insurer and extrapolating it over the market for forecasting or (outside in) by taking the deaths registered in a target location and then adjusting the forecast for the profile of people buying policies with the insurer.
But instead, we had a typical mentality of a kid who when given a hammer thinks everything is a nail. Since there is data available, a model was built. On this topic, do you know "the salary of a product manager is inversely proportional to the unit price of the product." (findings from one of the models when I was a analytics infant).
Tuesday, October 18, 2011
Analytical Data Mart -- is a Myth
Over the past two years, I have observed an increasing number of RFPs which include setting up of analytical data marts as part of the scope. This is a disturbing trend. It shows that the analytical projects are driven by non-analytical expertise.
I dont blame the IT guys for the way the RFPs are designed. They take a typcial data warehouse / reporting approach. In this case the requirements are known and the data warehouse is expected to maintain and provide the data elements for the reporting needs. Analytics too follows similar analogy. We have an end requirement -- which may be lapse prediction and the predictors, say. And this requirement needs data elements. This is where the similarity ends. Before the model is developed, one does not know which of the data elements are needed for the end report. In fact, one of the objective of the model building is to identify the data elements that are significant contributors towards the event under consideration, the lapsation of a policy.
Vendors in the market strut analytical data models. It basically consists of 100s of variables and derived variables which are likely to play a role of a contributer to the observed event. The IT team following the sales pitch of such vendors often include a scope of creating an analytical data mart containing all the 100s of variables listed.
If a company has enough budget and time (and patience), it will be okay to create an analytical data mart of over 800 variables from multiple sources of data and involving complex transformations. But this is never the case.
Now consider the models built on this data mart. Any model used in business will hardly have more than 20 variables (both direct and derived). So the rest of the 780+ variables was wasted.
An ideal way would be to let the statisticians use data dumps to do the modelling activity. Once a model is developed and tested and found to be useful for business deployment, the need for productionizing is to make the 6 to 8 to 20 variables available for the scoring purpose. Compare this with creating a 800+ variable data mart -- the former is a much more practical approach.
I have not even dwelt on the process of modelling and data prepartion. Based on the objective being tested, the data preparation will differ hugely from model to model. Often the analytical data marts get ignored and the analysts goes back to data dumps for creating the analytical data set for modelling. See my earlier post on time stamped data sets for modelling (http://crmzen.blogspot.com/2010/03/time-factor-in-modeling.html) to understand the complexity in creating data for statistical modelling.
It will be good for the IT department and the data warehousing personnel to understand this difference in the analytical process. Especially since this difference is not subtle. It is not needed to wait for 12 to 18 months (or more) till the data warehouse is set up and populated for the analytical activity to begin. And, the return on investment is much higher with predictive analytics. When compounded with the quick turnaround, the returns multiply.
I dont blame the IT guys for the way the RFPs are designed. They take a typcial data warehouse / reporting approach. In this case the requirements are known and the data warehouse is expected to maintain and provide the data elements for the reporting needs. Analytics too follows similar analogy. We have an end requirement -- which may be lapse prediction and the predictors, say. And this requirement needs data elements. This is where the similarity ends. Before the model is developed, one does not know which of the data elements are needed for the end report. In fact, one of the objective of the model building is to identify the data elements that are significant contributors towards the event under consideration, the lapsation of a policy.
Vendors in the market strut analytical data models. It basically consists of 100s of variables and derived variables which are likely to play a role of a contributer to the observed event. The IT team following the sales pitch of such vendors often include a scope of creating an analytical data mart containing all the 100s of variables listed.
If a company has enough budget and time (and patience), it will be okay to create an analytical data mart of over 800 variables from multiple sources of data and involving complex transformations. But this is never the case.
Now consider the models built on this data mart. Any model used in business will hardly have more than 20 variables (both direct and derived). So the rest of the 780+ variables was wasted.
An ideal way would be to let the statisticians use data dumps to do the modelling activity. Once a model is developed and tested and found to be useful for business deployment, the need for productionizing is to make the 6 to 8 to 20 variables available for the scoring purpose. Compare this with creating a 800+ variable data mart -- the former is a much more practical approach.
I have not even dwelt on the process of modelling and data prepartion. Based on the objective being tested, the data preparation will differ hugely from model to model. Often the analytical data marts get ignored and the analysts goes back to data dumps for creating the analytical data set for modelling. See my earlier post on time stamped data sets for modelling (http://crmzen.blogspot.com/2010/03/time-factor-in-modeling.html) to understand the complexity in creating data for statistical modelling.
It will be good for the IT department and the data warehousing personnel to understand this difference in the analytical process. Especially since this difference is not subtle. It is not needed to wait for 12 to 18 months (or more) till the data warehouse is set up and populated for the analytical activity to begin. And, the return on investment is much higher with predictive analytics. When compounded with the quick turnaround, the returns multiply.
Monday, October 03, 2011
Statistics hints at Existence of God
At the onset of this post let me make a few things clear. I am not an atheist. I have faith in the bible. But I do not hesitate in questioning facts about the bible. Now, according to some, that makes me an atheist. Atleast, it does not make me a fanatic. So I leave it at that.
My professor of economics, Mr. Sakhalkar, once made a statement that when one reads he should not be selective. That creates a bias and restricts ones circle of influence. Going down that path a couple of years ago took me down the path of the origins of religion.
A very interesting fact came to the conscious. "God" was an invention of man to blame someone for things that man did not understand and could not control. In the old days, the most frightful element for man was fire. He could not understand it, he could not control it and it was most destructive force. So a Fire God existed. And among all the gods, the Fire God was the most powerful one. There was Water God, Land God, Wind God, Sun God, Star God and so on.
As man started understanding the elements of nature, the importance of that God diminished. Until the God itself was abolished. Eventually as we sit in the twenty-first century, almost all of the element Gods are extinct. When the Gods started disappearing, man found reason to blame other men for various elements. So a forest fire was because some fool dropped a lighted cigarette on dry grass. Understanding man and its nature became a prime topic of importance. God now starting taking form of man. A convenient person to blame when things go beyond explanation.
A statistical model is a function which describes the observed behaviour based on identified independent variables. But what most sales personnel (call them consultants or statisticians) leave out is the "epsilon" (E). Every function in statistics has the epsilon attached to it. Consider the following function which forecast the amount of sale at a retail outlet.
Y = aX + bZ + ε
where Y is the amount of sale, X is the average salary of store visitors and Z is the fact that it is raining. ε represents the epsilon or the error component. This is statisticians' way of keeping themselves legally safe (yup... statisticians are smarter than lawyers). It implies that though the function predicts the amount of sale, there is an error component which explains the deviation in actual amount against the predicted amount. So if the actual sales is different from the predicted amount, blame the error component and not the statistician.
There is a whole lot of effort expended in trying to understand and explain this error component. New variables found, new algorithms applied, but the ε still lives on. Till date there has not been any statistics model that does not have the ε in it.
Even a statement that "All crows are black." will be stated by a statistician as "It is with 95% level of confidence that 99% of the time all crows are black." This is with the understanding that if someone sees a crow with is not all black, the statistician is safe with his statement.
So now we have a EPSILON which is the unexplained factor and responsible for all the deviations in the statistical model. In some cases, like predicting the likelihood of a patient surviving a critical operation, this EPSILON also represents a dangerous and frightening probability. A play in the equation that is unexplained and blamed for any deviation in our predictive capabilities. EUREKA ---- we have found the "STATISTICS" GOD.
My professor of economics, Mr. Sakhalkar, once made a statement that when one reads he should not be selective. That creates a bias and restricts ones circle of influence. Going down that path a couple of years ago took me down the path of the origins of religion.
A very interesting fact came to the conscious. "God" was an invention of man to blame someone for things that man did not understand and could not control. In the old days, the most frightful element for man was fire. He could not understand it, he could not control it and it was most destructive force. So a Fire God existed. And among all the gods, the Fire God was the most powerful one. There was Water God, Land God, Wind God, Sun God, Star God and so on.
As man started understanding the elements of nature, the importance of that God diminished. Until the God itself was abolished. Eventually as we sit in the twenty-first century, almost all of the element Gods are extinct. When the Gods started disappearing, man found reason to blame other men for various elements. So a forest fire was because some fool dropped a lighted cigarette on dry grass. Understanding man and its nature became a prime topic of importance. God now starting taking form of man. A convenient person to blame when things go beyond explanation.
A statistical model is a function which describes the observed behaviour based on identified independent variables. But what most sales personnel (call them consultants or statisticians) leave out is the "epsilon" (E). Every function in statistics has the epsilon attached to it. Consider the following function which forecast the amount of sale at a retail outlet.
Y = aX + bZ + ε
where Y is the amount of sale, X is the average salary of store visitors and Z is the fact that it is raining. ε represents the epsilon or the error component. This is statisticians' way of keeping themselves legally safe (yup... statisticians are smarter than lawyers). It implies that though the function predicts the amount of sale, there is an error component which explains the deviation in actual amount against the predicted amount. So if the actual sales is different from the predicted amount, blame the error component and not the statistician.
There is a whole lot of effort expended in trying to understand and explain this error component. New variables found, new algorithms applied, but the ε still lives on. Till date there has not been any statistics model that does not have the ε in it.
Even a statement that "All crows are black." will be stated by a statistician as "It is with 95% level of confidence that 99% of the time all crows are black." This is with the understanding that if someone sees a crow with is not all black, the statistician is safe with his statement.
So now we have a EPSILON which is the unexplained factor and responsible for all the deviations in the statistical model. In some cases, like predicting the likelihood of a patient surviving a critical operation, this EPSILON also represents a dangerous and frightening probability. A play in the equation that is unexplained and blamed for any deviation in our predictive capabilities. EUREKA ---- we have found the "STATISTICS" GOD.
ε
Friday, September 02, 2011
The Don Quixote in the Marketing Department
While reading Don Quixote, an interesting thought crossed my mind while on the chapter where the character prepares to go on his mission. The knight had made a helmet and tested it with his lance. The helmet broke on the first contact. Thereafter, I quote from the book --
"He did not like its being broke with so much ease, and therefore to secure it from the like accident, he made it anew, and fenced it with thin plates of iron, which he fixed in the inside of it so artificially, that at last he had reason to be satisfied with the solidity of the work and so, without any experiment, he resolved it should pass to all intents and purposes for a full and sufficient helmet."
In case you have not noticed, that is one single sentence. I caught myself chuckling when I was reading the text matter. Not from the confidence of the knight in the book but from remembering some of my discussions with marketing people. At one such discussion with a CMO, I was presenting a plan to execute the campaign. The initial phase was to test the campaign offer in a pilot. The CMO was aghast at this suggestion. He said that they know their customer and he knows what they want and the offer is the best that could happen to his customers. He wanted us to guarantee a minimum uptake on the offer. Since there was no history of similar offers neither was there any results of any testing on the offer, I refused to guarantee unless he agrees to do a pilot campaign. The CMO refused and I did not pick up the assignment. Needless to say, the CMO did not last long in the company.
At another assignment that I was involved for a promotion campaign, the client had designed a "intersting" campaign for his customers. On discussing, I found out that the campaign was "interesting" because people who heard about it found it interesting. These people were apparently collegues from other departments. I did a quick dip-stick and found that no one from my project team are the customers of the client. That is, no body bought their products. Now, when I discussed the promotion with my team members, they sure found it interesting. Then, I made one of them call up the office boy who was manning the reception desk to explain the promotion. The office boy was confused and wondered if he had intercepted a key message from the extra-terrestrials (okay I am over doing this last part). I asked the office boy if he bought the products of the client. He said yes and he did not seem too keen on the promotion. When I took this finding to the client, they just blew into my face. I asked them to repeat the exercise with the security guard. But the client refused to go ahead with the experiment and moved on to other activity in the execution plan. It would not be a surprise that the promotion did not perform as per expectation.
These two scenarios reflected the Don Quixote mindset in the real world. Sometimes we are so confident on what we believe will work with the customer that we just refuse to do any test marketing. It is a surprise that when one launches a new product, there is a whole lot of science applied to the pilot launch. But when it comes to campaigns, everyone just believes the campaign offer is the best idea and wants to execute it immediately. Is it because a new product has hundreds of crores of rupees spent on it whereas a campaign would relatively cost only a couple of crores of rupees? But if one clubs all the campaign costs as well as the costs of opportunities lost when a customer signs for do-not-disturb or moves to the competitor, the combined cost will eventually overrun the development cost.
At one telco, we were discussing with the campaign manager on his campaign activities. This person had recently run a "successful" campaign selling 100 Rupee voucher to people who recharge with 50 Rupee voucher. For this, he was giving 15 Rupee talk time free. His definition of success was he sold 30 Crore Rupee worth of recharge vouchers. When asked how does he know that the same customers would have anyhow bought the 100 Rupee voucher or more without any offer and he would have perhaps sold 38 crore Rupee worth of recharges, he was stumped. We persisted, highlighting that he has given off atleast 30% of the revenue in free talk time which further increased the cost of the offer. We told him, he should have test/control the offer before launching it. He was so angry with us and refused to meet us for the next two months. The communication restarted when he ran into some problem on new campaigns and wanted help. So he called us back for a discussion. Well, the prodigal son deserves a feast... so we went to meet him.
So many Don Quixotes in real life. This reminds me of a recent post on a social platform. The post was from a "vegetarian" guy who was angry because his grocery store sent him offers on non-vegetarian fare. He was upset that the store did not bother to check that he has NEVER bought a non-vegetarian item from the store ever.
"He did not like its being broke with so much ease, and therefore to secure it from the like accident, he made it anew, and fenced it with thin plates of iron, which he fixed in the inside of it so artificially, that at last he had reason to be satisfied with the solidity of the work and so, without any experiment, he resolved it should pass to all intents and purposes for a full and sufficient helmet."
In case you have not noticed, that is one single sentence. I caught myself chuckling when I was reading the text matter. Not from the confidence of the knight in the book but from remembering some of my discussions with marketing people. At one such discussion with a CMO, I was presenting a plan to execute the campaign. The initial phase was to test the campaign offer in a pilot. The CMO was aghast at this suggestion. He said that they know their customer and he knows what they want and the offer is the best that could happen to his customers. He wanted us to guarantee a minimum uptake on the offer. Since there was no history of similar offers neither was there any results of any testing on the offer, I refused to guarantee unless he agrees to do a pilot campaign. The CMO refused and I did not pick up the assignment. Needless to say, the CMO did not last long in the company.
At another assignment that I was involved for a promotion campaign, the client had designed a "intersting" campaign for his customers. On discussing, I found out that the campaign was "interesting" because people who heard about it found it interesting. These people were apparently collegues from other departments. I did a quick dip-stick and found that no one from my project team are the customers of the client. That is, no body bought their products. Now, when I discussed the promotion with my team members, they sure found it interesting. Then, I made one of them call up the office boy who was manning the reception desk to explain the promotion. The office boy was confused and wondered if he had intercepted a key message from the extra-terrestrials (okay I am over doing this last part). I asked the office boy if he bought the products of the client. He said yes and he did not seem too keen on the promotion. When I took this finding to the client, they just blew into my face. I asked them to repeat the exercise with the security guard. But the client refused to go ahead with the experiment and moved on to other activity in the execution plan. It would not be a surprise that the promotion did not perform as per expectation.
These two scenarios reflected the Don Quixote mindset in the real world. Sometimes we are so confident on what we believe will work with the customer that we just refuse to do any test marketing. It is a surprise that when one launches a new product, there is a whole lot of science applied to the pilot launch. But when it comes to campaigns, everyone just believes the campaign offer is the best idea and wants to execute it immediately. Is it because a new product has hundreds of crores of rupees spent on it whereas a campaign would relatively cost only a couple of crores of rupees? But if one clubs all the campaign costs as well as the costs of opportunities lost when a customer signs for do-not-disturb or moves to the competitor, the combined cost will eventually overrun the development cost.
At one telco, we were discussing with the campaign manager on his campaign activities. This person had recently run a "successful" campaign selling 100 Rupee voucher to people who recharge with 50 Rupee voucher. For this, he was giving 15 Rupee talk time free. His definition of success was he sold 30 Crore Rupee worth of recharge vouchers. When asked how does he know that the same customers would have anyhow bought the 100 Rupee voucher or more without any offer and he would have perhaps sold 38 crore Rupee worth of recharges, he was stumped. We persisted, highlighting that he has given off atleast 30% of the revenue in free talk time which further increased the cost of the offer. We told him, he should have test/control the offer before launching it. He was so angry with us and refused to meet us for the next two months. The communication restarted when he ran into some problem on new campaigns and wanted help. So he called us back for a discussion. Well, the prodigal son deserves a feast... so we went to meet him.
So many Don Quixotes in real life. This reminds me of a recent post on a social platform. The post was from a "vegetarian" guy who was angry because his grocery store sent him offers on non-vegetarian fare. He was upset that the store did not bother to check that he has NEVER bought a non-vegetarian item from the store ever.
Thursday, August 11, 2011
ATM eating cash!!! A lost opportunity for CRM...
Mumbai Mirror's 10th August edition has a cover page article that screamed about an ATM that eats up the customer's cash. On reading further, apparently someone had tinkered with the ATM machine such that it would debit a higher amount than what was actually withdrawn. In one of the cases mentioned, the customer withdrew Rs. 10,000 but was debited for Rs. 40,000. Another customer made a transaction of Rs. 50,000 but was debited for Rs. 200,000 thousand.
The article has generated a decent amount of comments on how ATMs are tinkered with.
In all this melee, there was something the bank, in this case Axis Bank, could have done. I am not going to lecture on how ATMs can be made more secured. That is not my area of expertise.
In a career spanning close to two decades, I have delivered multiple projects. As with every software project, the User Acceptance Test phase is the final stage wherein the end users test the software before signing it off for deployment. During every UAT, I always set some ground rules:
1. It is a system made by man and can definitely be broken by man.
2. If your objective is to break the system, you will definitely succeed and it is not a commendable thing to achieve.
I use the same rules for this scenario. The ATM has been designed by man and so can be broken by man. There is a manual process involved where access it permitted to a person and thus opens environment for tinkering.
In line with CRM, the question is what could the Bank have done?
In both cases mentioned, the customer was the one to complain to the bank. No doubt the bank would have refunded the money to the customer. But what about the customer who did not get the SMS message or did not check his account soon enough?
This is a perfect case for event or transaction based analysis. In both scenarios, withdrawal of such a large amount may not have been a regular transaction for the customer. In fact for the second case, withdrawal of Rs. 200,000 may have been a first.
The bank could have analysed the debits for each customer and been able to identify the unusual withdrawal by the customer. Based on past behaviour each customer may have a different threshold for identifying an unusual behaviour. The moment this unusal behaviour was identified, the bank should call the customer and confirm the withdrawal. When the customer denies the transaction, it would point to possible fraud. The bank would have various options now:
-- deactivate the debit card
-- noticing the ATM machine to be the same one, decommission it immediately so more customers do not face the trouble.
From a customer perpsective, the bank could have assured the customer that the transactions will be actively investigated and the amount credited back to the account if valid.
The benefit to the bank was that the customer would be comfortable thinking that the bank is looking into his case as well as the bank could have limited the customers exposed to the fraudulent ATM. And more important, imagine if the press article said -- that the bank identified the fraud and quickly protected more customers from facing the same by blocking the ATM. Now that article would be "priceless".
The article has generated a decent amount of comments on how ATMs are tinkered with.
In all this melee, there was something the bank, in this case Axis Bank, could have done. I am not going to lecture on how ATMs can be made more secured. That is not my area of expertise.
In a career spanning close to two decades, I have delivered multiple projects. As with every software project, the User Acceptance Test phase is the final stage wherein the end users test the software before signing it off for deployment. During every UAT, I always set some ground rules:
1. It is a system made by man and can definitely be broken by man.
2. If your objective is to break the system, you will definitely succeed and it is not a commendable thing to achieve.
I use the same rules for this scenario. The ATM has been designed by man and so can be broken by man. There is a manual process involved where access it permitted to a person and thus opens environment for tinkering.
In line with CRM, the question is what could the Bank have done?
In both cases mentioned, the customer was the one to complain to the bank. No doubt the bank would have refunded the money to the customer. But what about the customer who did not get the SMS message or did not check his account soon enough?
This is a perfect case for event or transaction based analysis. In both scenarios, withdrawal of such a large amount may not have been a regular transaction for the customer. In fact for the second case, withdrawal of Rs. 200,000 may have been a first.
The bank could have analysed the debits for each customer and been able to identify the unusual withdrawal by the customer. Based on past behaviour each customer may have a different threshold for identifying an unusual behaviour. The moment this unusal behaviour was identified, the bank should call the customer and confirm the withdrawal. When the customer denies the transaction, it would point to possible fraud. The bank would have various options now:
-- deactivate the debit card
-- noticing the ATM machine to be the same one, decommission it immediately so more customers do not face the trouble.
From a customer perpsective, the bank could have assured the customer that the transactions will be actively investigated and the amount credited back to the account if valid.
The benefit to the bank was that the customer would be comfortable thinking that the bank is looking into his case as well as the bank could have limited the customers exposed to the fraudulent ATM. And more important, imagine if the press article said -- that the bank identified the fraud and quickly protected more customers from facing the same by blocking the ATM. Now that article would be "priceless".
Friday, August 05, 2011
Let HRD solve Marketing Issues.....
Recently I viewed the video of the presentation of Deborah Rhodes during her appearance at TED. During the speech she has quoted Malcolm Gladwell stating "The only time a physician and a physicist get together is when the physicist gets sick". She goes on to state that this occurence "makes no sense, because physicians have all kinds of problems that they don't realize have solutions. And physicists have all kinds of solutions for things that they don't realize have solutions." Before I continue with my post, I want anyone who has a woman to love in their life (and thats practically everyone) to view this talk by Deborah titled "A tool that finds 3x more breast tumors, and why it's not available to you."
What Malcolm Gladwell says is so very true. If you look around your office and see groups of people hudled in the conference rooms, there is a 9 out of 10 chance that they belong to the same department. They have probably got together to solve some problem or address some issue related to operations of the department.
Organizations define Key Performance Indicators and allocate them to various departments. So revenue is sales. Costing is finance. and so on.... Thereafter, these KPIs are the babies of each department and no body else is allowed to play with the baby or provide tips to the foster parents.
At one telco, there was a high amount of customer churn in the landline business after the first 3 months of activation. The role of keeping the customer active belonged to the "Retention Department." There was a whole lot of action happening in the retention department. I was called in to see if statistics could play a role. Having just two months of customer behaviour data did not excite he statistician in me. I decided to snoop around while I was at the premises of the company. I was also building CRM processes in line with eTOM for this telco. As part of this assignment, I was walking the process with the team responsible for installing the landline phones at the consumer site. One of this person stated that the sales person would ask the customer to just sign the acquisition form and would fill it up later in the office. While filling the form, the sales person would tick all options and services to be activated. When this person went for installation, the consumer would only be interested in knowing about voice calls since that was all he wanted. However, when the bills came in, the consumer saw an 'inflated' bill since he was also charged for services that he did not need. The installation person stated that he could not help the consumer since the installation process did not allow him to revalidate the consumer services and to deactivate the ones the consumer does not need.
This discussion connected the dots. The consumer saw a high amount on his bill for just 'voice telephony.' To him, the telco was overcharging him. Nobody explained to him the rentals charged for services that were activated for him because the sales person ticked the options in the application form. The consumer got upset over this payment and would request for disconnection in the second month. Before he could be disconnected, the telco required him to pay his outstanding till date. So a second bill was generated. This showed that majority of consumers churned in the third month.
If only, the retention department had involved every one who had a consumer touch point in trying to understand the problem at hand.
For that matter, the Human Resources and Finance departments may also have some solutions to the problems of say, the Marketing department.
What Malcolm Gladwell says is so very true. If you look around your office and see groups of people hudled in the conference rooms, there is a 9 out of 10 chance that they belong to the same department. They have probably got together to solve some problem or address some issue related to operations of the department.
Organizations define Key Performance Indicators and allocate them to various departments. So revenue is sales. Costing is finance. and so on.... Thereafter, these KPIs are the babies of each department and no body else is allowed to play with the baby or provide tips to the foster parents.
At one telco, there was a high amount of customer churn in the landline business after the first 3 months of activation. The role of keeping the customer active belonged to the "Retention Department." There was a whole lot of action happening in the retention department. I was called in to see if statistics could play a role. Having just two months of customer behaviour data did not excite he statistician in me. I decided to snoop around while I was at the premises of the company. I was also building CRM processes in line with eTOM for this telco. As part of this assignment, I was walking the process with the team responsible for installing the landline phones at the consumer site. One of this person stated that the sales person would ask the customer to just sign the acquisition form and would fill it up later in the office. While filling the form, the sales person would tick all options and services to be activated. When this person went for installation, the consumer would only be interested in knowing about voice calls since that was all he wanted. However, when the bills came in, the consumer saw an 'inflated' bill since he was also charged for services that he did not need. The installation person stated that he could not help the consumer since the installation process did not allow him to revalidate the consumer services and to deactivate the ones the consumer does not need.
This discussion connected the dots. The consumer saw a high amount on his bill for just 'voice telephony.' To him, the telco was overcharging him. Nobody explained to him the rentals charged for services that were activated for him because the sales person ticked the options in the application form. The consumer got upset over this payment and would request for disconnection in the second month. Before he could be disconnected, the telco required him to pay his outstanding till date. So a second bill was generated. This showed that majority of consumers churned in the third month.
If only, the retention department had involved every one who had a consumer touch point in trying to understand the problem at hand.
For that matter, the Human Resources and Finance departments may also have some solutions to the problems of say, the Marketing department.
Tuesday, July 19, 2011
Choice is Good... but too much of it is BAD
The TVC for a noodle brand shows a kid asking a series of questions to arrive at the fact that choice is good.
There have been a lot of arguments in favour of providing choices. It leads to personalization of offers. One can target greater population. A seller can provide more options. And finally, the customer feels empowered and in control of the buying process when he can select and decide the item to purchase from various options available.
I would advise the product managers and marketers to exercise caution when providing options. Let’s walk through the customers’ mental buying process. For sake of example, we will consider an item which is fast becoming a frequent purchase – a mobile handset.
When a customer has decided to purchase a new handset, there is a set of features and functionality that forms a checklist in his mind. He looks at various options available and shortlists those models that meet the mandatory and sufficient needs from this check list. Finally, he zeroes on one model and purchases the same.
What happens next is very interesting. Have you ever considered why you are dissatisfied after you buy a product?
When the customer has purchased the product, his universe of options now reduces to just two. The first option is the model he has recently purchased and the other option is a “collation” of all other models. So it is now a comparison between one model and the “best features” of all the remaining models that was originally being compared. When this evaluation plays in his mind, he obviously feels a doubt that his decision was not correct and he feels disappointed. Sometimes this process happens even while the purchase is being processed. Ever noticed that slight tinge of doubt on your decision and purchase while your credit card swipe is being authorized?
Most often this disappointment gets translated into dissatisfaction with the product purchased and eventually with the supplier or manufacturer.
It is very important that the choices be kept at an optimum. Cause the fact there is a choice of options forces the customer to take one more decision. Any step in the buying process delays the sale and every step is a potential drop from the purchase process. Thus choices can delay the sales closure since the customer now has to perform one extra evaluation and take an additional decision. Even when a customer does make a decision, the post purchase evaluation will result in dissatisfaction with his decision. The blame will ultimately rest on the supplier / manufacturer. Hence, I reiterate, keep the choices at an optimum. Let there be a real reason for the option to exist.
In case of the noodle, whenever I walk down the breakfast aisle, I take the easy way out. I pick up one of each flavor and dump it in the shopping cart. That’s one less decision for me.
And as for the mobile handset, I still get the tingle that maybe the E72 was not the right handset to buy…sigh!!! Especially when I use my wife’s phone … an E5 from the same manufacturer at 60% the cost…sigh! sigh!!. Ford was so right… any colour as long as it is black.
If you read this, do leave your feedback / comment.
There have been a lot of arguments in favour of providing choices. It leads to personalization of offers. One can target greater population. A seller can provide more options. And finally, the customer feels empowered and in control of the buying process when he can select and decide the item to purchase from various options available.
I would advise the product managers and marketers to exercise caution when providing options. Let’s walk through the customers’ mental buying process. For sake of example, we will consider an item which is fast becoming a frequent purchase – a mobile handset.
When a customer has decided to purchase a new handset, there is a set of features and functionality that forms a checklist in his mind. He looks at various options available and shortlists those models that meet the mandatory and sufficient needs from this check list. Finally, he zeroes on one model and purchases the same.
What happens next is very interesting. Have you ever considered why you are dissatisfied after you buy a product?
When the customer has purchased the product, his universe of options now reduces to just two. The first option is the model he has recently purchased and the other option is a “collation” of all other models. So it is now a comparison between one model and the “best features” of all the remaining models that was originally being compared. When this evaluation plays in his mind, he obviously feels a doubt that his decision was not correct and he feels disappointed. Sometimes this process happens even while the purchase is being processed. Ever noticed that slight tinge of doubt on your decision and purchase while your credit card swipe is being authorized?
Most often this disappointment gets translated into dissatisfaction with the product purchased and eventually with the supplier or manufacturer.
It is very important that the choices be kept at an optimum. Cause the fact there is a choice of options forces the customer to take one more decision. Any step in the buying process delays the sale and every step is a potential drop from the purchase process. Thus choices can delay the sales closure since the customer now has to perform one extra evaluation and take an additional decision. Even when a customer does make a decision, the post purchase evaluation will result in dissatisfaction with his decision. The blame will ultimately rest on the supplier / manufacturer. Hence, I reiterate, keep the choices at an optimum. Let there be a real reason for the option to exist.
In case of the noodle, whenever I walk down the breakfast aisle, I take the easy way out. I pick up one of each flavor and dump it in the shopping cart. That’s one less decision for me.
And as for the mobile handset, I still get the tingle that maybe the E72 was not the right handset to buy…sigh!!! Especially when I use my wife’s phone … an E5 from the same manufacturer at 60% the cost…sigh! sigh!!. Ford was so right… any colour as long as it is black.
If you read this, do leave your feedback / comment.
Thursday, July 07, 2011
Happy to be PETER
Finally I got to contributing to my blog again. My earlier company had stopped me from publishing in my personal blog and expected me to contribute to the official blog. For some reason this bought about the most dreadful thing to writers -- A writers Block. I just could not get to write any more ... any where. A change of job resulted in change of mindset and I am back in action here.
Today I write about online insurance. Recently I bought a term insurance online. One of the reasons, I went online was the very low premium. Initially I was sceptical about the low premium and thought maybe the claim process will not be good. But somehow I convinced myself to get a policy online.
The past few days I did some research on the online v/s offline policies being sold. Some insurers have similar policies being sold online as well as offline (via agents). But there is a huge difference in the premiums being charged. I thought it might be the savings on the agent commission and selling expenses. But then, that is high only in the first year, whereas the premium is a constant low throughout the policy term.
A lot of research and reading various articles by insurance experts and the following came about:
1. People buying online are educated guys.
2. Educated guys are more knowledgeable about health issues.
3. Guys buying online are likely to be in white collar jobs.
4. White collar job workers have lower mortality rates than the blue collar job workers.
So the expected claim ratio from online policies are much lesser and as such the insurers can charge much lower premiums.
Which means, when I bought the policies offline (via agents), I was clubbed with the general population and ended up paying a higher premium to offset the losses from the segments with higher mortality experience. This reminds me of my earlier article Robin Hood Pricing wherein I had highlight how good customers end up subsidizing the bad customers. Today, the insurer treats the online policy buyers as a separate market and does not club it with the rest of the population. The cost of serving the online policy customer is less and as such the premiums are lower.
Now as I hold my policy documents I feel happy to be Peter and happy that the insurer did not rob this Peter to pay some Paul.
Today I write about online insurance. Recently I bought a term insurance online. One of the reasons, I went online was the very low premium. Initially I was sceptical about the low premium and thought maybe the claim process will not be good. But somehow I convinced myself to get a policy online.
The past few days I did some research on the online v/s offline policies being sold. Some insurers have similar policies being sold online as well as offline (via agents). But there is a huge difference in the premiums being charged. I thought it might be the savings on the agent commission and selling expenses. But then, that is high only in the first year, whereas the premium is a constant low throughout the policy term.
A lot of research and reading various articles by insurance experts and the following came about:
1. People buying online are educated guys.
2. Educated guys are more knowledgeable about health issues.
3. Guys buying online are likely to be in white collar jobs.
4. White collar job workers have lower mortality rates than the blue collar job workers.
So the expected claim ratio from online policies are much lesser and as such the insurers can charge much lower premiums.
Which means, when I bought the policies offline (via agents), I was clubbed with the general population and ended up paying a higher premium to offset the losses from the segments with higher mortality experience. This reminds me of my earlier article Robin Hood Pricing wherein I had highlight how good customers end up subsidizing the bad customers. Today, the insurer treats the online policy buyers as a separate market and does not club it with the rest of the population. The cost of serving the online policy customer is less and as such the premiums are lower.
Now as I hold my policy documents I feel happy to be Peter and happy that the insurer did not rob this Peter to pay some Paul.
Sunday, January 23, 2011
One question too many....
After 4 years of using my Sony Ericsson M600i (yup..the one profiled in Casino Royale), I switched to a Nokia E72 last week. Reviews said this was the best business phone in the market today. I am not getting into a debate on that one.
While setting up the phone without referring to the user manual, I somehow managed to get my SIM blocked. This state is not new to me, since I had achieved the same state with my M600i. So I called up the Vodafone customer service number. After the initial queries, I was directed to the action menu of the IVR. I was surprised to hear that the "Know your PUK" option was the second option. So I choose it and get the IVR read out my PUK. I got my E72 running again. All within 2 minutes. Considering I had a harrowing time during my M600i days to get the PUK from the Agent of Vodafone. This was a very pleasant experience. When I hung up, I was very happy to get my E72 alive so I can proceed on my exploration of the features.
Within a few minutes, I get an SMS from Vodafone:
"Thank you for using Vodafone Interactive Voice Response(IVR) System.Was the required information for your query available on IVR?Reply toll free with YES or NO."
It was very appropriate time from them, and I replied a resounding "YES".
Then I get a second SMS,
"Thank you for your response.Was the IVR menu easy to use?Reply toll free with YES or NO."
Now this was the last straw. It got me pissed off. And I have still not responded to this. This was one question too many. Vodafone should have stopped at the first question. Maybe the next time I call them, they could have asked this. "One question at a time" is my motto that I preach to every CRM manager I meet.
While on this, let me highlight the "toll free" phrase in both messages. Vodafone has recently started charging for speaking to the call center agent. Bold move? I say stupid move. You can only do this, if your services are up to the mark and your service permits self service. The fact that they have to throw of customers from talking to the call center agents shows that customers do not find Vodafone services meeting their needs.
At this time, Idea comes out the "Get Idea" advert showing Abhishek telling a woman to get Idea when she has been held in waiting by the customer service number. Will it help them get the Vodafone customers...? This needs to be seen. But for someone who has recently been thru the Vodafone customer service and possibly suffered a charged interaction with the agent, this ad is bang on. A review of the advert series in this Sunday's daily by two advertising professionals gave poor rating to the Idea ad series. But as a consumer I disagree and think the advert series is bang on and probably much better that the "language" series Idea ran previously.
Yesterday I received a SMS from Nokia about a "strong BLACK theme" available for free download. When I go to the link, I am told that my phone does not support this theme. My registration with Nokia was for E72. They should have known that the theme is not supported by my phone and should have eliminated my number from the SMS list.
I have heard many marketers say "its only SMS and costs only 1 paise to send one out". But the cost of a wrong message is the possible option for "do not mail". To me the TCO of any database marketing should also include the cost of a customer opting for a "do not contact". Then this one SMS may seem like a cost of over a 100 rupees. Now let me hear you, Mr. Marketer..... speak louder...
While setting up the phone without referring to the user manual, I somehow managed to get my SIM blocked. This state is not new to me, since I had achieved the same state with my M600i. So I called up the Vodafone customer service number. After the initial queries, I was directed to the action menu of the IVR. I was surprised to hear that the "Know your PUK" option was the second option. So I choose it and get the IVR read out my PUK. I got my E72 running again. All within 2 minutes. Considering I had a harrowing time during my M600i days to get the PUK from the Agent of Vodafone. This was a very pleasant experience. When I hung up, I was very happy to get my E72 alive so I can proceed on my exploration of the features.
Within a few minutes, I get an SMS from Vodafone:
"Thank you for using Vodafone Interactive Voice Response(IVR) System.Was the required information for your query available on IVR?Reply toll free with YES or NO."
It was very appropriate time from them, and I replied a resounding "YES".
Then I get a second SMS,
"Thank you for your response.Was the IVR menu easy to use?Reply toll free with YES or NO."
Now this was the last straw. It got me pissed off. And I have still not responded to this. This was one question too many. Vodafone should have stopped at the first question. Maybe the next time I call them, they could have asked this. "One question at a time" is my motto that I preach to every CRM manager I meet.
While on this, let me highlight the "toll free" phrase in both messages. Vodafone has recently started charging for speaking to the call center agent. Bold move? I say stupid move. You can only do this, if your services are up to the mark and your service permits self service. The fact that they have to throw of customers from talking to the call center agents shows that customers do not find Vodafone services meeting their needs.
At this time, Idea comes out the "Get Idea" advert showing Abhishek telling a woman to get Idea when she has been held in waiting by the customer service number. Will it help them get the Vodafone customers...? This needs to be seen. But for someone who has recently been thru the Vodafone customer service and possibly suffered a charged interaction with the agent, this ad is bang on. A review of the advert series in this Sunday's daily by two advertising professionals gave poor rating to the Idea ad series. But as a consumer I disagree and think the advert series is bang on and probably much better that the "language" series Idea ran previously.
Yesterday I received a SMS from Nokia about a "strong BLACK theme" available for free download. When I go to the link, I am told that my phone does not support this theme. My registration with Nokia was for E72. They should have known that the theme is not supported by my phone and should have eliminated my number from the SMS list.
I have heard many marketers say "its only SMS and costs only 1 paise to send one out". But the cost of a wrong message is the possible option for "do not mail". To me the TCO of any database marketing should also include the cost of a customer opting for a "do not contact". Then this one SMS may seem like a cost of over a 100 rupees. Now let me hear you, Mr. Marketer..... speak louder...
Subscribe to:
Posts (Atom)
