Well-executed customer relationship management (CRM) and customer data analytics can significantly boost revenue and profits. How do CRM principles apply to search engine marketing (SEM)? We know CRM and customer analytics uncover small segments of the overall customer base that contribute a disproportionate percentage of revenue or profit.
You may have heard of the Pareto Principle (often called the 80/20 rule). It holds true for almost every company’s data. Sometimes the data is astounding, going far beyond 80 percent value delivered by 20 percent of the customer base.
At a recent Frost and Sullivan event, CRM evangelist Martha Rogers shared a particularly interesting example of the power of customer analytics. According to car rental industry research, the top 0.2 percent of all customers rent 25 percent of all cars. Wow. That’s taking analytics to the next level. Marketers must tap the power of these “super customers.” To do so, we take an analytic approach:
- Identify super customers you already have.
- Treat them right (you can’t afford to lose them).
- Determine what attributes identify them. What sets them apart from lesser-value customers? Attributes may include psychographics, demographics, behavior, preferences and needs; tenure as customers; and the Holy Grail for marketing optimization — how did these super customers become customers? Which advertising or marketing channel delivered them?
- Develop a plan to poach from the competition by serving the super customer better.
- Capture super customers at the beginning of their need for your service or product, then cultivate them and foster loyalty.
SEM can help with steps four and five (competitive customer acquisition and new customer acquisition) and may even help with step two. The answer’s in analytics.
I hope you use analytics to identify the most efficient portions of your search marketing campaign, to find the keywords, engines, and listings that deliver the immediate post-click behavior you seek (orders, registrations, or branding). Many marketers optimize campaigns by post-click conversion behavior, set cost per order (CPO) or cost per action (CPA) objectives based on immediate profit on each product, average shopping cart sizes, or other short-term monetary metrics. You can go further.
Consumer behaviors continue long after the initial purchase, registration, or branding experience. In a best-case scenario, long-term behavior is what you must track. Your mission (should you choose to accept it) is to determine the following:
- For e-commerce businesses, do some listings generate shopping cart averages greater than estimated when setting target CPOs?
- Do some listings deliver more extra-value customers who produce higher profits or revenue than average?
- Do leads from some listings deliver a greater percentage of new customers than others? This occurs in business-to-business (B2B) and high-involvement purchases where customers go through an involved sales cycle.
- Do leads from some listings deliver new customers who order more over time? Look at lifetime customer value.
- Do some listings deliver repeat customers who don’t order exclusively from you but are reminded of you when they see a search listing? For example, “switchers” are indifferent shoppers who can be persuaded by environment and price. Think Coke/Pepsi in the grocery store.
If the Pareto Principle holds for you, a small percentage of your customers deliver the lion’s share of profits. Do some super customers come from search listings? If a segment of your search listings delivers super customers, aren’t those listings more valuable?
Average acquisition costs and average cost of customer acquisition can be misleading. Managing by averages may not build solid business. What if we apply lessons learned by top CRM practitioners? What if we could not just determine CPO or cost per lead when managing campaigns but also predict the lifetime value of a customer and use that information to run a more efficient campaign?
Therein lies an opportunity to tap CRM for improved efficiency. Of course, most marketers don’t have the ability to tie long-term user profiling information to campaigns with many individual elements. One can argue most campaigns are integrated across multiple media, so simply knowing the final touch point doesn’t mean boosting emphasis on the last presales touch point raises sales.
Customers have a buying cycle. You may be communicating to them differently at each point in the cycle.
Yet for many marketers, incremental high-value customer acquisitions are possible through final-stage analysis. Some eCRM and analytics companies have this capability, but I don’t advise you to go install one of these products simply because you have an opportunity to optimize a search campaign. A simpler analysis may provide enough information to allow you to apply CRM principles and the Pareto Principle to all your media.
Set CPO and CPA targets taking into account more short-term profits. Know your super-customer profile. You optimize for immediate profit by listing (and possibly by daypart). Consider adding simple analytic systems that tie long-term behavior to all marketing, online and off-.
Even if you don’t have the analytics to support CPO/CPA decisions, sometimes your gut leads you in the right direction. Say you sell medical supplies. Among your products are adult diapers and insulin test kits (products people buy repeatedly). Unless fulfillment or pricing disappoints your customer, that customer is likely to provide long-term order flow. Knowing this, raise CPO targets for some product-related listings.
Less-obvious situations include buyers for other products or search listings that generate unusually large shopping cart totals. Do these indicate higher lifetime value? Ask your tech team if it can do some simple user profiling. Attach the media source ID to customer IDs, then crunch the numbers. You may be pleasantly surprised.
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