Thursday’s Wall Street Journal had a quote from Carol Bartz, the CEO of Yahoo, “Are we leading up to “I’m both too old and too stupid to know what the Internet is’?” Her remark was in response to a question about her experience but it made me think about a potential generational gap in Internet usage.
At a book club meeting almost a year ago, several members asked for a description of Twitter, as if it was a foreign country or new-fangled religion they had heard about. One member provided an excellent summary based on his usage of the site but several were left trying to get their heads around why anyone in their right mind would use Twitter. Once again Twitter came up during a recent book club meeting. No one new had tried out the service in the 10 months since our last discussion. It made me wonder if the technological gap is not just rich versus poor but also young versus old. As the remark by Carol Bartz indicates, there is a general perception that the Internet is a young person’s game. High profile anecdotes have reinforced that assumption. According to a July 2008 Frank Rich Op Ed piece in the New York Times, John McCain doesn’t know how to use a computer.
For marketers, this represents a challenge and an opportunity. To me, it is further proof that we need to develop integrated campaigns with both online and offline channels for outbound communication and inbound response. You cannot assume that everyone will be on the Internet 24/7. Broadcast media, print ads, direct mail, etc. can play an important role in reaching an older audience that may not be on the Internet as frequently and they reinforce your message to those who are active on the Internet. A recent report found that displaying a URL within a Yellow Pages print ad drove an increase in online leads. Of course, you should measure the interaction of online and offline behavior to see what drives the most responses and to optimize future campaigns.
Modeling is a powerful tool that is worth considering when determining how best to spend your marketing dollar. At its simplest, modeling looks for patterns in data to predict future behavior. That data could be past behavior. If someone bought diapers last week, it is very likely they will buy them again this week. It could also include demographics such as age and gender or, in a B2B context firmographics, the number of employees and annual sales volume. Attitudinal information, such as willingness to purchase a product, could also be used in a model. The power of modeling comes from the fact that it weighs all of the factors and results in a unique algorithm that predicts future behavior. Instead of the usual “spray and pray” approach, modeling enables you to focus your dollars where they will have the most effect.
Two articles in the Wall Street Journal last week offered real life examples of how models can solve business problems. I have seen clients use attrition models and proportional hazard models to determine which customers are likely to leave. Google is building an attrition model to identify which of its employees are most likely to leave the company for another opportunity. Presumably Google will target those employees most likely to leave and be able to retain valuable talent that might otherwise walk out the door.
Chrysler’s digital agency has designed a media modeling system according to the Wall Street Journal. It sounds like a marketing mix model and is being used to allocate Chrysler’s marketing dollars. At a basic level, this model tells Chrysler how much money needs to be spent on marketing to drive a certain number of vehicle sales based on the web traffic generated. By monitoring online activity and tying it to their marketing campaigns, Chrysler has determined how many web visits translate into sales. The media modeling system, including enhancements based on the ongoing performance of television advertisements, has helped Chrysler determine how to structure their marketing campaign and tweak marketing in real time to drive results.
These two examples may not fit your exact situation but they highlight the power and value of modeling.
Let’s face it. It takes time and patience to develop a good e-mail subscriber list. First, you have to make it easy for individuals to add and update their e-mail addresses. Second, every time you e-mail them, you run the risk that they might unsubscribe. Third, maintaining the e-mail list requires that you clean the file (e.g., remove hard bounces), e-mail frequently to keep subscribers engaged and send targeted, timely and relevant e-mails.
It is not surprising then that I am routinely asked about purchasing e-mail addresses. My standard answer is to be prepared to pay a lot and to get few responses relative to your investment. A recent Limeduck post illustrates what can happen when you purchase e-mail addresses.
Accountable marketing is a lofty goal. It is the idea that marketing can and should be measured. It sounds simple but is difficult to implement and execute. It starts with planning and identifying metrics for success up front and ends with calculating ROI and other relevant metrics as well as incorporating lessons learned into future marketing efforts.
I have written about metrics before. In fact, my New Year’s Resolutions post included a suggestion to test, measure and learn. Even in social media there are now agreed upon metrics. The Interactive Agency Bureau (IAB) has released social media ad metric definitions.
Given the current tough economic climate, there is no reason not to measure and evaluate your marketing efforts. How else can you know what worked, what did not work and whether your efforts have met your threshold or definition for success?