Profitable manufacturers are often known for production efficiency. Refrigerators are built on a different production line versus dishwashers, microwaves, or ovens. While that works great for manufacturing efficiency, siloed marketing efforts by product type is not an effective approach to marketing. Unfortunately, we often see our clients who work in the manufacturing industry doing just that.


Recently, one of our clients, a large appliance manufacturer came to us looking to improve post-purchase customer experience and influence brand loyalty. To do this, we began to dig into the data to try to identify key data points to inform our strategy. We determined that looking at customer reviews would be a great place to start. The idea here was to look at review data to determine who has had a positive experience and would be more likely to purchase again or identify poor reviews to gain insights on how to improve those experiences.


To start, we identified the set of customer data that could help us create our audience segments. As we started to look at their data, we uncovered a major issue (that we frankly see quite often) that we knew we needed to solve before we could implement any new strategies. Rather than having a centralized view of behavior at an individual customer level, their data profiles were built at the product level. That meant that if Person A owned two of their products, Person B owned two of their products and Person C owned one product, rather than appearing in the database as:

Person A - Has purchased:

  • Product 1
  • Product 2

Person B - Has purchased:

  • Product 3
  • Product 4

Person C - Has purchased:

  • Product 5


… there were five unique instances in their database! Something like this…

Product 1 - Purchased by:

  • Person A

Product 2 - Purchased by:

  • Person A

Product 3 - Purchased by:

  • Person B

Product 4 - Purchased by:

  • Person B

Product 5 - Purchased by:

  • Person C


They had a lens on their data that was product first and customer second. This meant that they would literally treat each product purchase as if it was a unique instance of a customer. In the sample example above, the data implied that there were five different customers and 5 products instead of the three customers who had purchased a total of five products. Why is this an issue? Because with incomplete and disparate customer accounts you run the risk of communication redundancy and you are limited in your ability to fully understand customer behavior and preferences.


Flipping the Orientation


What could we do to address the problem? Simply put, we flipped the orientation. We took the same source data and we flipped it to tie product data to a consumer profile versus tying customer data to a specific product first. Now, the company can target messaging at a customer level, rather than just the product level. They can now answer…

  • What products does an individual own?
  • Do they own one product or multiple products?
  • Have they given their product reviews?
  • Have they given good reviews or bad reviews?
  • Do they own a microwave and a refrigerator, or do they just own a microwave?


Flipping the data orientation enabled these types of insights and allows you to target marketing efforts at the unique consumer-level vs the product level. With a consolidated customer view, the brand is now able to gather more precise customer insights to deliver more relevant, targeted messages to the audience segments who are most likely to engage. This includes understanding which products an individual owns or does not own to more efficiently target prospects to gain a greater ‘share of the wallet’ aka brand loyalty.


Cross-selling for “Share of Wallet” vs Individual Product


While our client had originally approached us for strategic execution recommendations, we knew that data enablement would be the key to help us solve their problem around customer experience and brand loyalty. With customer-focused data now enabled, the company can create much more cohesive marketing strategies. Rather than focusing on individual products, the brand can craft marketing campaigns that focus on gaining ‘share of the wallet’ to encourage brand loyalty and additional purchases. Previously the company did not have insight into all the products owned by an individual which made it challenging to cross-sell. It would be a poor customer experience to try to sell a microwave to a refrigerator owner if they already owned one you just had not connected the dots. With this data enabled, the company can now connect the data to understand all the products someone owns and behaviors they have taken across channels. They can target people who have purchased refrigerators but do not own other products and persuade them to buy a microwave. For the customers who have not yet given a review, they can now target them and persuade them to give a review. This centralized customer view allows for more targeted, relevant messaging and limits the risk of redundant marketing which had been resulting in poor customer experience.

The results?

A positive and dramatic increase in both the quality and quantity of consumer sentiment. (To the tune of a 114% YTY increase in reviews!)

Before you launch your next big marketing campaign, ask yourself, could we be doing more with our customer data? If you need a second opinion, we can help!