Archive for the ‘Consumer Behavior’ Category

How Predictive Analytics Optimizes Frugal Environments

Thursday, February 19th, 2009

I am a bit discouraged today. I am surprised that we have not had more takers on our free customer scorecard application. Granted we have not unleashed the Social Media channel on the tool but I figured that after a week of availability we would have 10% more customers. The customers that have used it are overwhelmingly surprised of the results but I still wonder if the tool’s purpose is clear.

One of the leading, and might I say insightful, retail marketing professionals, Kelly Mooney, recently posted a blog titled: “Myths about online Retail Marketing”. In the blog she does a great job of providing an analysis of several marketing myths and there are a couple of takeaways that directly support how we perceive our tools to add value.

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Product Placement Ads Much Better

Thursday, January 15th, 2009

Well not definitively but some research by cognitive scientist Mark Changizi (R.P.I) suggests that product placement advertising actually makes a person desire to obtain the product more so than if one were to see a 30 second advertisement 10 times in a week for the same product. Why is this?

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Predictive Analytics Provide Big Payouts For Early Adopters

Thursday, November 6th, 2008

I was reading up on analytics technology today and ran across an interesting article at TDWI (The Data Warehousing Institute) which surprised me.  It was surprising due to the fact that it was a year old but was reporting the same results as today:  predicitve analytics solutions are still novel to many companies and unknown to even more.  Even after dozens, if not hundreds, of successful case studies show how predictive analytics are a low-effort, high ROI solution to help a company achieve strategic goals:

[P]redictive analytics can yield a substantial ROI. Predictive analytics can help companies optimize existing processes, better understand customer behavior, identify unexpected opportunities, and anticipate problems before they happen,” Eckerson writes. For six years running, he points out, a majority of TDWI’s annual Leadership Award winners have used predictive analytic solutions to achieve noteworthy business results.

Before we created our predictive analytics solution for email marketing we knew the benefits of predictive analytics solutions and we realized that marketing has many metrics and data points as well as a very strong set of historical data which we can and do use to build solid, accurate models of customer behavior and desire.   Why are users of predictive analytics still considered Early Adopters?

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Marketing CSI

Thursday, October 30th, 2008

The other day I was flipping through the channels and landed on an episode of CSI.  I forget which flavor, it looked sunny and beachy so it was probably not the one in New York City.   Anyway, in this episode a murder took place and the only evidence seemed to be a passerby’s recollection of a license plate and hair color of the driver.  Not much to start with but as we all know that is enough for the CSI team.  

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Customer Analytics: Why You Should Get Started Now

Tuesday, September 16th, 2008

I wanted to briefly build upon Doug’s posts about customer analytics over the past few days (see Customer Analytics: A Guide To Getting Started). I try to keep abreast of the latest research about customer analytics that gets published and, just this week, came across the new Aberdeen Group’s report on the subject (Customer Analytics: Segmentation Beyond Demographics). While I encourage you to read the whole report, I wanted to point out some of the info and metrics in the article that I found most compelling.

First, and most impressive, companies with full customer analytics implementations saw incredible gains across the board, including:

  • 43% year over year increase in annual revenue
  • 42% year over year increase in customer profitability
  • 35% year over year increase in average order value
  • 25% year over year increase in market share growth

And lest you think that only those companies that completely overhauled their systems saw improvements, companies that have started down the customer analytics path saw, on average, a 7% year over year increase in annual revenue and a 3% year over year increase in customer profitability. While these might seem like modest gains, companies without a customer analytics system in place actually saw a decrease in customer profitability year over year.

Second, best in class organizations are using a wider range of data in more ways than other organizations. What do I mean by this? Well, to begin with, they’re collecting more data about their customers -demographic and behavioral information from web analytics, crm, email marketing, and customer feedback tools, all of it stored in one easily accessible place. And, they’re making better use of this data through the creation of enhanced segmentation (meaning segmentation that uses more than just behavioral or demographic info to assign customer to groups) and more relevant indicator metrics (i.e. CLV) that better inform sales and marketing staff about their customers.

Lastly, the report highlights how important it is to invest in customer analytics now. With over half of all the companies the Aberdeen Group talked to for this report planning on increasing their spending budget for customer analytics in the next year (that number goes up to 60% for companies that are considered best in class), if you haven’t made an investment in a customer analytics yet, you simply can’t wait any longer or you’ll soon find yourself far behind competitors.

Luckily, Doug’s posts can walk you through the basics on getting started, but I wanted to make sure to point out some of the most recent information on how important it is to get up and running now.

What is Customer Analysis?

Monday, June 9th, 2008

Customer analysis is the process of determining customer segmentation, value, purchasing behavior and motivation in order to better target marketing and increase sales. Well, that sounds ok in theory but is perhaps a bit too abstract for practical use. Practically speaking, what is customer analysis, really?

What is customer analysis

The crux of customer analysis is that all customers are not created equal. Companies have some customers who are worth their weight in gold. They buy frequently and spend a lot. They are a pleasure to deal with: no returns, no complaints, no hassles. They also have customers who make life miserable. They inundate customer service centers with calls and constantly return merchandise. They buy infrequently and are happy to take their business to a competitor if it means they can save a dollar.

The top 20% of customers are the lifeblood of a business and contribute 80% of the profit. The bottom 20% at best contribute nothing to the bottom line, and at worst cost more than they contribute.

The purpose of customer analysis is to identify the top 20% of customers (gold customers), middle 60% (silver customers) and bottom 20% (lead customers). We then try to determine how to keep the gold customers happy and how to encourage silver customers to become gold customers. Then we have to figure out what to do with our lead customers.

We can do a basic customer analysis in four steps:

1. Who are my customers? Which customers are valuable? Which aren’t?

There are many ways to determine a customer’s value. One of the most accepted from is using a metric called customer lifetime value (CLV). CLV estimates how much a profit customer will contribute over his/her “lifetime”. By comparing CLVs among customers (or more often, among customer segments), we get a good idea of which customers are valuable and which are not.

Another method that can be slightly easier to use is a recency, frequency, monetary analysis. This method breaks customers into groups based up on how often they purchase, how much they spend on average, and how long it’s been since their last purchase. Customers who rank high in all three criteria are most valuable while those that rank low are least valuable.

Over the next few weeks we’ll talk more about these techniques and how to use them. The general idea, though, is that we separate our customers into gold, silver, and lead groups based on how much profit we expect them to contribute.

It is important to note that the gold, silver, and lead groups are not customer segments. Customer segments are a function of demographics and behavior, not value. Our gold customers can be made up of many different segments and the customers who comprise a particular segment may differ wildly in how much money they spend.

To make things a bit more confusing, customer segments can also have CLVs associated with them. Assigning a CLV to a customer segment is a useful technique in determining how much to spend to acquire a customer in that segment. We’ll touch on this more in step 4.

2. What do I do with my most valuable customers?

Congratulations! You’ve identified your lifeblood customers. These customers feel like they have a relationship with you and buy based on this relationship, not on price. From a marketing perspective they are already “maxed out”. You can’t spur them to spend any more with you — they are already giving you all of their business! All you can do is make sure that they are stay happy.

The single biggest mistake in marketing to these customers is to give them discount offers. These customers do not make their decision to purchase with you based on price. By giving them discount offers you simply throw money away and, worse, train these high value customers to wait until they receive a discount offer before buying.

One of the best ways to market to your gold customers is to offer perks that are not available to other customers. This is essentially what airlines do with their status levels. By treating these customers as special, they will be more likely to continue spending with you to maintain their special status.

Sometimes, however, it can be appropriate to give these customers special offers that aren’t necessarily discounts. This is something we will discuss in a future post.

3. How do I make less valuable customers more valuable?

We have to face facts. Some customers are too far gone to save. Lead customers are money losers. It is almost always best to stop spending marketing dollars on them. If you can entice them to go to your competitor it is a double win — not only do you get rid of a money losing customer, but now your competition is saddled with them.

The majority of your marketing budget should be spent trying to move your silver customers up to gold customers. This is where the real action happens. You can entice customers to step up their spending with a clever combination of incentives, promotions, and discounts. Since each segment can be expected to respond differently to your messaging, however, it is critical to really understand what drives these customers to buy. Often the best way to find the optimal marketing mix and message is through rigorous testing and analysis. No fun, maybe, but the payoff is huge if done correctly.

Again, we’ll talk about specific testing techniques in a future post.

The simple rule in customer acquisition is that you want to spend money to acquire customers who look like your current gold customers. These are the customer segments that are most represented in your gold group. It’s ok to spend to acquire silver customers, too, as long as the cost per customer is less than the expected lifetime value of the potential new customer.

This high level view of customer analysis is a good starting point for companies who are looking to use their customer data to increase sales and get better ROI from their marketing budgets. By following these 4 simple steps you’ll be well on your way to understanding your customers and better targeting your marketing spend.