Case Study One ABB June 02, 2014 Monsanto Group
ABB Case Study One Question: Based on the Descriptor Data tab of the spreadsheet about the location of customers and the sales potential of each account or prospect ALONE , to what companies would would you direct the new direct direct marketing program? Specify the accounts and customer, or prospect type.
1.) Immediately, we would go through the ABB Descriptor Data and note the companies with the highest annual spend at ABB. It is logical to assume that these companies are existing ABB customers and are already utilizing ABB as a primary provider of goods. We would then try to note any correlations with annual spend and the district in which the customer is located. To make the data more approachable, we sorted the ABB Descriptor Data table with the following filters: Firm Chosen (A = ABB) Annual Purchase Volume (Highest to Lowest) District (Highest to Lowest) which yielded the following results:
44 11 37 42 21 57 58 54 3 50 69 13 61 41 45 87 24 38
Customer 44 11 37 42 21 57 58 54 3 50 69 13 61 41 45 87 24 38
Ann. Purchase Volume ($ K) $10,997 $1,722 $767 $752 $749 $736 $700 $660 $643 $584 $528 $466 $462 $444 $415 $395 $322 $182
District 2 3 2 1 3 1 3 1 2 3 1 2 3 1 1 2 1 2
Firm Chosen A A A A A A A A A A A A A A A A A A
It can be seen that of the 88 responses provided by customers in ABB’s area, 18 of these responders are already working with ABB. Furthermore, 11 of the 18 existing customers are spending over $500,000 per annum on ABB goods which demonstrates segment loyalty in our opinion. To increase market share, ABB would benefit mostly from maximizing its “competitive segment’s” potential spend and taking customers from competitors. Of ABB’s existing customers we customers we would shift our attention to the bottom 7 existing customers (customers 13 – 38 – 38 on the list above) to direct the new marketing program to increase their existing annual purchase volume. Next, we would shift our attention to winning over non- existing customers. In deciding on which non-customers we would direct the new marketing program to, we would take note of which districts ABB is already enjoying the most success in and focus marketing efforts in these districts as ABB’s brand has clearly been established here.
42 57 54 69 41 45 24 44 37 3 13 87 38 11 21 58 50 61
Cust Cu stom omer er Volu Volume me ($ K) 42 $752 57 $736 $660 54 $528 69 $444 41 $415 45 $322 24 $10,997 44 37 $767 3 $6 $643 13 $466 $395 87 $182 38 $1,722 11 $749 21 $700 58 $584 50 61 $462
Dist Distri rict ct 1 1 1 1 1 1 1 2 2 2 2 2 2 3 3 3 3 3
Chos Ch osen en A A A A A A A Total Spend District 1 $3,857 A A A A A A Total Spend District 2: $13,450 A A A A A Total Spend District 3: $4,217
From the table above, ABB has its highest volume of customers in District 1, which interestingly is the district with the lowest annual purchases. However, District 2 is by far the leader in annual dollars spent with District 3 just edging out District 1. This trend is perpetuated with ABB’s competitors. The table below presents the amounts purchased by NON customers in each district. District
Annual Purchases by Competitors (in 000's)
1 2 3
$19,502 $40,189 $21,544
TOTAL
$81,235
To gain market share (and win over new customers), ABB would benefit greatly from focusing its marketing program in District 2 as this represents half of the total market sha re enjoyed by ABB’s competitors in addition to being the District that ABB already enjoys the most success in with its current customers. The data shows that there are several customers who despite investing in ABB equipment would still choose a different firm. The ABB marketing program should focus their attention to these customers so that ABB will be their primary choice. The marketing strategy will have to be executed in different districts for different customers. These customers have the highest annual purchase volume (above $1M) with ABB and yet still prefer ABB’s competitors as first choice. The table below specifies.
Customer 35 43 66 32 84 17 74 20
Ann. Purchase Volume ($ K) $14,798 $12,514 $9,793 $6,270 $1,404 $1,364 $1,219 $1,009
District 2 2 3 1 3 3 1 2
Firm Chosen Edison Westinghouse GE Westinghouse GE GE GE GE
2. Which variables are the key drivers of choice in t his market?
Variables / Coefficient estimates Energy Loss Quality Price Prob Solver Solver Warranty Maintenance Ease of Install Const-1 Spare Parts rts Const-2 Const-3 Baseline
Coefficient estimates 2.655609373 2.639411874 2.180581123 2.032180072 1.140702152 0.59369178 0.520022504 -0.12379144 -0.1 -0.13 32620299 -0.671217439 -0.687234929
Standard t-statistic deviation 0.673705707 0.673705707 3.941794387 3.941794387 0.687749269 0.687749269 3.837753079 3.837753079 0.586578426 0.586578426 3.717458784 3.717458784 0.54967 0.54967581 581 3.69705 3.69705203 2037 7 0.330994613 0.330994613 3.446286152 3.446286152 0.437028185 1.358474809 0.172875214 0.172875214 3.008080166 3.008080166 0.678548909 -0.182435544 0.21 .217569998 -0.6 -0.60 09552329 0.719410204 -0.93301073 0.715046053 -0.961105829 n/a n/a
Based on the above table, the key drivers of choice in this market are (in order of ranking): 1. 2. 3. 4. 5. 6.
Energy Loss Quality Price Problem Solver Warranty Ease of Install
Although “Maintenance” has a positive value estimate, it is not statistically significant. B. Based on your analyses, analyses, on which firms firms would you focus focus your efforts? Why?
Based on our analysis, we would focus on our efforts efforts on GE and Westinghouse. We would focus on these companies because improvements in ABB variables shows the elasticity’s to have the greatest impacts on these companies. The table below illustrates the top 4 keys drives.
Elasticitie Elasticitiess of Energy Loss L oss Elasticities of Quality Elasticitie Elasticitiess of Prob Solver S olver Elasticities of Price
ABB
GE
Westinghou Westinghouse se
Edison Edison
4.64383 4.64383625 6254 4 4.31740 4.31740946 9462 2 4.09800 4.09800744 7443 3 3.63461 3.63461523 5238 8
-1.516862 -1.516862885 885 -1.284260 -1.284260603 603 -1.298963 -1.298963958 958 -1.161306 -1.161306586 586
-1.28 - 1.28784 784424 4244 4 -1.305749 -1.305749559 559 -1.18 - 1.18065 065432 4321 1 -1.022970 -1.022970805 805
-0.724631 -0.724631277 277 -0.677423 -0.677423272 272 -0.628140 -0.628140544 544 -0.576942 -0.576942029 029
3. Assume the marketing marketing efforts targeted at companies in the Loyal and and Lost categories result in no incremental gain. On the other hand, suppose that you could retain or win half the companies in the Switchable and Competitive segments segments with this program. How much improvement improvement in sales productivity can you realize by applying this choice model to the allocations of your efforts?
We determined the competitive competitive and switchable groups utilizing two means. The first method was to look at the Predicted and Observed choices on the Estimation tab. We took customers who were predicted ABB and chose a competitor as well as customers who were not predicted as ABB but chose ABB and placed them into this this pool of customers to focus. The second method method was to look only at the probabilities. We sorted the ABB column column to only show probabilities below below 70% and above 30%. We choose this because we felt probabilities above 70% were Loyal ABB customers and probabilities below 30% are Lost customers. We added all the customers from the two different methods and looked at the value for the annual purchase on the Descriptor Data Tab (see table below). The total amount of customers was 15% of the market share. We added the annual purchase price of all the customers and took 50% of that value since the question stated to assume we can win or retain half the customers. With this method, we can improve our sales productivity by $50,000.
Customer
Ann. Purchase 4 7 11 13 16 26 36 37 41 50 61 84 86
Total 50% Total
$ $ $ $ $ $ $ $ $ $ $ $ $ $ $
562 664 1,722 466 894 899 511 767 444 584 462 1,404 480 100,126 50,063
4. What other recommendations would you offer to ABB Electric to improve its segmentation marketing program?
ABB Electric should protect its market share by monitoring the “ABB Electric Loyal Segment”. Segment ”. I would recommend using the Estimation Sample Details tab to analyze which customers reside in this “loyal” loyal” segment. The marketing team at ABB Electric can leverage the customer probability data to define which customers are “loyal” to ABB’s power transformers and transformers and should be marketed to when it comes time to repurchase transformers. transformers. Using this data the decision maker can efficiently use sales resources with the goal of making these customers lifetime buyers and defending their market share.
The chart above is an example of customers that would be ideal to protect. Customers in this segment have a higher probability that they would buy from ABB Electric rather than the next closest competitor. With a retention system in place will improve ABB’s retention rates and thus improving profitability. profitability. Proactively stopping a customer from leaving is far easier than trying to win them back once they have left. 5. Comment on the uses and limitations limitations and possible extensions extensions of this modeling approach.
Regarding uses and limitations limitations adding fields that could be used to track loyalty would be a useful feature. Such data as: how long has a particular supplier supplier been used and have there been been any recent changes. Another data field that would be beneficial is tracking how and/or who the decision maker is for partners. Knowing how businesses make decisions decisions and who carries the most weight in this process will allow the company a strategic advantage in gaining and/or retaining the business. Finally, tracking historical data and setting a frequency, building data trends around this information to make efforts to improve percentages. Other possible extensions of this approach could be to narrow the focus down to the marketing of particular products. products . As well as, use the marketing program to develop an internal auditing system. Asking questions such as: “If we know we need to improve quality – what – what is affecting our quality in the first place?” or “If we need to improve our prices – how – how come our prices are high in the first place?” Using this data and thought thought processes we should be able to able to look inward and improve the overall product our company is putting out.
