By now it seems clear that matching product or service offers to the consumers who need them, want them and are ready to purchase is the best possible marketing practice. This is targeting, pure and simple. Among the many goals of target marketing, efficient use of resources is one of the most important, especially if you are a small or medium sized business – with limited marketing funds and few marketing staff. You’ve got the product and services ready to go, now who are the right audiences or segments to match up with? Let’s see how customer analysis can help.
Customer analysis can be applied to answer many different questions. Depending on what data you have on your customer – from demographic, geographic, firmographic to transactional and behavioral – you can understand what makes customer different or the same and most of all, what motivates their purchases. As a small or midsized company, SMB, you might not possess all of that data but if you are able to group your customers into some type of business category and match purchases against them, you can accomplish intelligent targeting for your offers.
Here’s how one company achieved intelligent targeting through the use of customer analysis : this B2B online company had thousands of members. It’s mission was to offer other small B2B companies growth through web hosting, domain registration, business email, content, advice on public relations and a host of other services. But monetization was its goal. The question was – who were best customers and how could they use target offers to find more? These are the steps the company took:
1. Customers were sorted by the number of products installed
2. Sorted customers were next matched by business category
3. Analysis showed which business categories represented the highest percent of installed products
4. It also showed what percent of the total customer base was represented by which business category
At that point, although they knew the break out of their business by category and number of products installed, they still didn’t know which customers were best customers by revenue.
5. By adding the third dimension of size, the company was able to visualize the size of the customers that were purchasing multiple products
The results were displayed on a 3 dimensional bubble chart which showed two interesting facts: relatively few business categories had multiple products installed, and, of those, 3 of 6 were among the smallest percent of the company’s total base. The other categories with multiple products installed were among the largest percent of total customer base.
What did this mean? This analysis allowed the company to create two targeting strategies:
- Those companies which comprised the largest percent of total base also were among the categories that purchased multiple products. It was concluded that these categories seem naturally inclined to buy anything the company produces. The strategy was to maximize the relationship with these customers to maintain their growth and value.
- Those companies which represent the highest percent of multiple products purchased, but are among the lowest percent of total base. It was clear that these were also desirable business categories and that the company needed more of them. This pointed to an acquisition strategy that might begin with an offer to incent trial, then purchase.
These strategies enabled the development of different messages and targeted offers. This small web portal company was also able to market more efficiently and effectively through the use of customer analysis and intelligent targeting.
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