Archive for the ‘Customer Loyalty’ Category

Read All About It: Why Newspapers Need Marketing Analytics

October 26, 2010

After nearly 20 years, I decided to let my subscription to the Wall Street Journal lapse. A few months ago, I did likewise with my longtime subscription to the Chicago Tribune. I didn’t want to end my subscriptions, but as a customer, I felt my voice wasn’t being heard.

Some marketing research and predictive modeling might have enabled the Journal and the Tribune to keep me from defecting. From these efforts, both publications could have spotted my increasing frustration and dissatisfaction and intervened before I chose to vote with my feet.

Long story short, I let both subscriptions lapse for the same reason: chronic unreliable delivery, which was allowed to fester for many years despite numerous calls by me to their customer service numbers about missing and late deliveries.

Marketing Research

Both newspapers could have used marketing research to alert them to the likelihood that I would not renew my subscriptions. They each had lots of primary research readily available to them, without needing to do any surveys: my frequent calls to their customer service department, with the same complaint.

Imagine the wealth of insights both papers could have reaped from this data: they could determine the most common breaches of customer service; by looking at the number of times customers complained about the same issue, they could determine where problems were left unresolved; by breaking down the most frequent complaints by geography, they could determine whether additional delivery persons needed to be hired, or if more training was necessary; and most of all, both newspapers could have also found their most frequent complainers, and reached out to them to see what could be improved.

Both newspapers could have also conducted regular customer satisfaction surveys of their subscribers, asking about overall satisfaction and likelihood of renewing, followed by questions about subscribers’ perceptions about delivery service, quality of reporting, etc. The surveys could have helped the Journal and the Tribune grab the low-hanging fruit by identifying the key elements of service delivery that have the strongest impact on subscriber satisfaction and likelihood of renewal, and then coming up with a strategy to secure satisfaction with those elements.

Predictive Modeling

Another way both newspapers might have been able to intervene and retain my business would have been to predict my likelihood of lapse. This so-called attrition or “churn” modeling is common in industries whose customers are continuity-focused: newspapers and magazines, credit cards, membership associations, health clubs, banks, wireless communications, and broadband cable to name a few.

Attrition modeling (which, incidentally, will be discussed in the next two upcoming Forecast Friday posts) involves developing statistical models comparing attributes and characteristics of current customers with those of former, or churned, customers. The dependent variable being measured is whether a customer churned, so it would be a 1 if “yes” and a 0 if “no.”

Essentially, in building the model, the newspapers would look at several independent, or predictor, variables: customer demographics (e.g., age, income, gender, etc.), frequency of complaints, geography, to name a few. The model would then identify the variables that are the strongest predictors of whether a subscriber will not renew. The model will generate a score between 0 and 1, indicating each subscriber’s probability of not renewing. For example, a probability score of .72 indicates that there is a 72% chance a subscriber will let his/her subscription lapse, and that the newspaper may want to intervene.

In my case, both newspapers might have run such an attrition model to see if number of complaints in the last 12 months was a strong predictor of whether a subscriber would lapse. If that were the case, I would have a high probability of churn, and they could then call me; or, if they found that subscribers who churned were clustered in a particular area, they might be able to look for systemic breakdowns in customer service in that area. Either way, both papers could have found a way to salvage the subscriber relationship.


C-Sat Surveys Can Cause Intra-Organizational Conflict

October 20, 2010

I’ve grown somewhat leery of customer satisfaction surveys in recent years.  While I still believe they can add highly useful information for a company to make improvements to the customer experience, I am also convinced that many companies aren’t doing said research properly.

My reservations aside, regardless of whether a company is doing C-Sat research properly, customer satisfaction surveys can also cause intra-organizational friction and conflict.  Because of the ways departments are incentivized and compensated, some will benefit more than others.  Moreover, because many companies either don’t  link their desired financial and operational outcomes – or don’t link them well enough – to the survey, many departments can claim that the research isn’t working.  C-Sat research is fraught with inter-departmental conflict because companies are conducting it with vague objectives and rewarding – or punishing – departments for their ability or inability to meet those vague objectives.

The key to reducing the conflict caused by C-Sat surveys is to have all affected departments share in framing the objectives.  Before the survey is even designed, all parties should have an idea of what is going to be measured – whether it is repeat business, reduced complaints, shorter customer waiting times – and what they will all be accountable for.  Stakeholders should also work together to see how – or if – they can link the survey’s results to financial and operational performance.  And the stakeholders should be provided information, training, and guidelines to aid their managerial actions in response to the survey’s results.

Rankings – not Ratings – Matter in Customer Satisfaction Research

October 5, 2010

Companies spend countless dollars each year trying to measure and improve customer satisfaction. Much research has indicated that improved customer satisfaction brings about improved sales and share of wallet. Yet, the relationship is a weak one. Despite how satisfied customers say they are in customer satisfaction surveys, nearly 80% of their spending doesn’t relate to their stated satisfaction. Why is that?

In the Fall 2010 issue of Marketing Research, Jan Hofmeyr and Ged Parton of Synovate offer two reasons for this weak relationship between business results and satisfaction: companies don’t measure how their customers feel about competitors, nor do they recognize that they should be concerning themselves with the company’s rank, not its rating. For these reasons, the authors argue, models of what drives customer share of wallet offer little confidence.

Hofmeyr and Parton suggest some ways companies can make these improvements. Companies can start by getting ratings of the competition from the same respondent. If, for example, you are asking your customers to rate your company on a set of attributes that you believe are part of their customer satisfaction experience, if one customer gives a rating of “9” on a 10-point satisfaction scale, and another gives a rating of “8,” you are naturally inclined to treat the first customer as more likely to return and do business with you in the future. But that is only one piece of the puzzle, the authors say. What if you ask your customers to also rate your competition on those same attributes? What if the first customer assigns a competitor a “10” and the second customer a “7”? Basically what happens is that the first customer is very satisfied with your company, but even more satisfied with your competitor; the second customer may not be as satisfied with your company as the first customer, but he/she is most satisfied with your company over the competition. You’d probably want to spend more time with the one who gave the “8” rating.

In this example, the authors are essentially turning ratings into rankings. The ranking, not the rating, the author’s say, is the key to increased share of wallet. Hofmeyr and Parton’s research showed that if a customer shopped predominantly at two retailers, regardless of rating, as long as a customer rated one retailer higher than the other, then the top ranked retailer got an average of between 59% and 68% share of the customer’s wallet, while the lower ranked retailer got just 32% on average. If a customer shopped at three retailers, the pattern was similar: the top-ranked retailer got as much as a 58% share of the customer’s wallet; the second-place retailer, 25%, and the lowest ranked, 17%.

While it is important to have customers rate your company on satisfaction, it is just as important to have them rate your competition on the same evoked set and then order and rescale the ratings so that you can see where your company stands. By ranking your company with respect to your competition, you can much more easily determine gaps between satisfaction expectations and delivery so that you can increase share of wallet.

Former Customers Can Be Goldmine – Both in Marketing Research and Winback Sales

August 24, 2010

The other day, I stumbled across this May 28, 2010 blog post from MySmallBusinessMentor.com, which discussed how to re-activate former customers. While you should definitely reach out to former customers and try to get them to buy again, your former customers can also provide a wealth of information from a marketing research and process improvement standpoint.

If a customer has lapsed for, say a 90- or 180-day period, or a customer who used to buy once a month is now only buying every other month, reach out to that customer and mention that you noticed he/she isn’t frequenting your business as much, and ask if there’s anything with your company that they aren’t getting, or would like to see. It could be that they’re not happy with the product, or they found a similar, less expensive product from a competitor. Maybe they’ve “outgrown” your company’s products; or maybe they lost their job and can no longer afford it, whatever. You won’t know unless you ask.

For the purposes of marketing research, a lapsed customer can be more valuable than a loyal customer, especially when you consider that acquiring a new customer is six times more costly than retaining an existing customer. Taking the time to hear out a former customer can help you take corrective action to prevent other customer defections, improve your practices and product benefits, and even win back your lost customers.

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Was Marketing Research Absent from Liz Claiborne’s Strategy to Target Younger Consumers?

August 17, 2010

Yesterday’s Wall Street Journal reported that Liz Claiborne’s efforts to appeal to younger female consumers may have been the company’s downfall. This month, J. C. Penney will launch an exclusive line of Liz Claiborne clothing, home and accessories. As part of the agreement, Claiborne cedes control of production and marketing and converts the label into a mass market line in exchange for royalties, the article reported. In five years, Penney also has the option to buy U.S. rights to the Liz Claiborne name.

This may well be the concluding chapter in what appears to have been a failed attempt by Liz Claiborne to broaden its appeal to younger women. Apparently, Claiborne realized correctly it would need to move to a younger consumer, as most of its customers had been working age Baby Boomers, who have begun to retire. However, the Wall Street Journal indicates that its efforts to target the younger female consumer actually did more to harm the brand.

In trying to appeal to the younger crowd, Liz Claiborne nixed, sold off, or licensed out tried and true lines; it changed designs so much that it confused its existing customer base; it introduced lower priced items, eroding its appeal as a high-end brand; and it alienated its long-term relationship with Macy’s.

As I read the article, I couldn’t help asking myself whether Liz Claiborne did its homework. I don’t know whether Claiborne did or didn’t do marketing research, but deciding to pursue a new target market requires extensive marketing research, because so many mistakes can be made because of unaided judgment. Among other things, it is important to have surveyed the younger female shoppers to understand what they needed for workplace casual attire; and to have looked for common ground between existing product lines and the new, emerging fashions that the younger crowd was embracing. Most likely, the research would have led Claiborne to develop lines that were new enough to appeal to the younger working woman, but traditional enough to maintain loyalty with its existing boomer customer. If the research showed that the younger women wanted something drastically different in the way of style, then Claiborne could have used that information to develop a completely different line (likely by launching a whole different brand) aimed at those preferences.

When appealing to a new target market, it is also important to do pricing research. Surely younger consumers don’t have the discretionary income that older ones do. But that doesn’t necessarily mean a company should introduce lower-priced apparel. As Van Westendorp pricing theory suggests, a price can communicate one of four things to consumers: a good buy, a luxury item, an overpriced item, or a cheap, low-quality item. I could only wonder whether the introduction of lower priced merchandise might have led consumers to believe the newer lines of Liz Claiborne were of lower quality.

Companies that don’t conduct marketing research – or conduct it inadequately – increase their risk of failure, declining sales, customer defections, and increased competition.

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