Module 2 Case Study NBO
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"Data Analytics - Case Study"
By: Chad Bates
The Next Best Offer (NBO) programs are some of the best advertisement programs that companies have introduced in the last 25 years. These programs are even more critical today, because sometimes it seems like a revolving door of people when you go into a store. 20 years ago, we were accustomed to walking into a store, even a big box chain, and seeing the same person day in and day out. Those days are behind us, so retailers rely on data driven decisions and marketing to appeal to customers. I know because while working through high school and college, I was that person that people would come in to see to mix paint and help with hardware issues. This is how I met my wife’s mother for the 1
st
time too. I would be the one making suggestions to customers on brands, paint type, and quantity, but now we can analyze purchasing
data to help make those decisions. You do still find the people part of purchase decisions, in local and small businesses. Those businesses do not have the data, time, and purchase tracking to
make it effective to track peoples purchases. The small business relies on the personal interaction
between sales and customers to increase sales and customer retention. As nice it would be to come in and see Bill behind the paint counter whenever you go into Home Depot, we do not have that luxury anymore. NBOs can help drive sales and help forecast sales for the next quarter or even further out. NBOs can easily help predict the sales product based on purchase habits of consumers. At my previous employee we would use forecasting data to predict how much, which
products, and what kinds of soda we would need to make in order to meet the demand of the next
quarter. This data would have had to be taken directly from consumer purchase data from retailers. Using this data, we were able to predict how much soda we would need to produce to meet that demand. NBOs can also help predict product placement and substitutions. If one product is no longer available, it can help provide an alternative product based on your buying habits and preferences.
NBO programs are programs that analyze consumer data and make tailored recommendations. These programs allow the companies to keep customers and to increase the amount that these customers may spend with them. Some examples of these programs include Tesco rewards and tracking at stores, Zappos personalized purchase options, and Redbox personalized rental options. I really liked how Tesco would offer discounts for diapers, wipes, and beer for new parent reward members. This is a next level marketing strategy. Not only are you offering items essential for a newborn, but you are also taking care of the parents who are also going through a change. Using the data from the rewards cards, Tesco was able to determine that the new parents need the items and provide them with the NBO. Zappos is another great example of an NBO with shoe suggestions based on customer data. Every time you
click on something, add it to the cart, or purchase an item, that information is tracked and stored for someone to analyze and interpret based on those customer decisions. My wife who purchases most of her shoes from Zappos falls victim to this, if you can call it that, to the data collected from her clicks on the site. Now when she logs in, she is flooded with suggestions based on her previous purchases and items added to the cart. Sometimes these NBO suggestions can make it easier for customer to find what they are looking for. In the internet age, there are a million different varieties and styles available on retailers’ websites. The NBOs makes it easy for customers who like what they like and have those options pop right up in front of them instead of
having to browse through hundreds of items that they may not like. This is what Redbox has done for their customers at the height of the video rental kiosk. Based on customer rentals and frequency, they were able to offer suggestions and offer discounts for multiple rentals. NBOs use the data that was being kept by retail giants to help drive sales and steer customers to different products.
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To be effective with NBOs there must be some background data and important steps must
be taken to ensure that the NBO is effective. The first step in the process is to define the objectives. What does the company want to do with the NBO, increased market share, increase revenue, or increased loyalty? These important questions must be ascertained to effectively use an NBO to target the specified consumer. The example in the case study for this was Tesco and their goal of increasing the range of customer’s purchases and targeting regular customers on regular purchases. After you define the objective, they need to gather data. Without the data, you
have nothing, you must know your customers, offerings, and purchase content. Knowing your customers is sometimes as simple as gathering the data when they sign up for the loyalty programs and input the information when they sign up. Knowing your offerings can be a bit more difficult. When you are a larger retailer and purchase a large volume of product from different manufactures, it can be hard to make sure everything is uniform when it comes to the description. One company may label something as shorts and another one may label it at capris, unfortunately the retailer purchasing does not have control over that. The NBO needs to factor in
the purchase content. The perfect examples given in the case study are offering mortgages at ATMs and offering products during a customer complaint. These are not effective ways of offering products or services and will not have a positive effect on the consumer. Next the company must analyze and execute. Companies can offer simple suggestions based on buying or streaming habits such as: People also enjoyed buying this or watching that. Restaurants can use this to offer marketing campaigns targeting specific groups of people or certain proximity to other things such as schools and government buildings. Finally, companies must use NBOs and learn and evolve. You cannot stay consistent where you are while everything is changing around
you. You must continue to analyze the data and interpret it as you get it, as it could change week to week or year to year. When companies are looking to gather and categorize data from websites or rewards cards, they use Statistical Package for Social Sciences or SPSS. This software allows the market research team to categorize and organize the data in a way that researchers can analyze and use. The SPSS modeler will allow the market research team to analyze the data that was collected and
then use it to predict buying or purchasing patterns of the people that the data was collected on. In the lecture video we can see that the key demographic is married females. This was the primary demographic represented in the data set that was provided for the modeler. Which if you look at this from strictly a commonsense standpoint, it makes sense that the demographic would be married females. I know as a married male would not shop at Macys, but more than likely Rural King or Bass Pro. Maybe this is what Macy’s go-to demographic is because they advertise
more to them than they would a singe male. I know that my mom and my wife get coupons and emails from Macy’s almost every week. We can see from the modeling tree that customer satisfaction and gender are the best predictor for sales. Education and advertisement influenced the sales the least. With this data we can help create strategies to help drive sales now that we have identified what demographic we are catering to. This allows market researcher to focus more on the gender and satisfaction instead of education and advertisements to increase sales. Data drives the world, most of us know that with all the data we see and have collected on us in our everyday lives. Data is used in many ways also, it is used to drive sales, predict customer satisfaction, and provide customers with more products that they are interested in. NBO with the help from SPSS modeling can help companies, if they are smart, to drive sales and
advertise where it makes the most sense. If Bass Pro is looking to increase sales, then it can look
at sales and analyze who is making the purchase and what they are purchasing. For example, if they are seeing that males are purchasing more Under Armour clothes, then they can run marketing campaigns to males only about Under Armour Sales. If they also see they are selling more of a certain product, then they may want to order more of that and less of something like Adidas, that is not selling. Marketing teams can use the data gathered from websites to help predict where and how their sales may come. They can see if sales are coming from more in store
or coming online. These are all items that the SPSS modeling can help predict. Data makes the world go round, but you must know what to do with it when you have it. Dhingra, K. (2023). Corporate Social Responsibility and sustainability of corporate performance.
Jindal Journal of Business Research
, 12
(1), 19–29. https://doi.org/10.1177/22786821231161416 Davenport, T., Leandro DalleMule, & Lucker, J. (2014, October 28). Know what your customers want before they do
. Harvard Business Review. https://hbr.org/2011/12/know-what-your-
customers-want-before-they-do University of Illinois, Springfield (n.d). Analytics workshop-Part 1(narrated version) [video].
https://uispringfield.instructure.com/courses/10681/pages/analytics-workshop-part-1-
arrated-version?module_item_id=564193
University of Illinois, Springfield (n.d). Analytics workshop-Part 2(narrated version) [video].
ttps://uispringfield.instructure.com/courses/10681/pages/analytics-workshop-part-2
narrated-version?module_item_id=564194
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