As an entry-level consultant, my answer was easily measured in billable hours.  As the years progressed, I added sales assists, direct sales, increased brand recognition, and sales calls to that measurement.  But nowadays the answer is a little more cloudy.

In many industries, the economic slowdown means longer sales cycles, smaller contracts, and thinner margins.  The supply of available labor is larger than demand, so customers can afford to be choosy and spend more time scrutinizing credentials. Eager for work, companies are often willing to work for free in hopes of proving their worth and securing a deal down the road; my firm has been conducing 1-2 day free workshops to help clients develop their ideas and learn how our experience can help.

Personally, I have been spending my evenings and bench time focused on creating intellectual capital, developing and executing marketing campaigns, and developing and leading some of these workshops.  We all know that investing a brand, whether through mass media or face-to-face interactions, leads to longer-term value for the company, its clients, and its employees – but at the end of the exercise, have we really made any money for the company that day?

Most of my engagements over the past year or so have involved restructuring and cost reduction.  On these projects, we focus not only on lowering the cost base to match demand, but also on investing in areas where we see demand potential or where key capabilities should be developed to position the company for emerging trends.  Companies are willing to accept lower margins now in exchange for better products, positioning, and margins when the economy turns and demand recovers – but they’re also interested in better measurement systems to evaluate progress along the way and identify when to adjust course.

My company is no different; I recently launched a program to leverage bench resources to accelerate the development of intellectual capital so that we can increase our brand recognition, stay ahead of emerging trends, and develop our employees’ skills.  Our metrics are robust; it takes a steady volume of relevant IC to feed the marketing pipeline, resonate with potential buyers, setup sales calls, and deliver winning proposals.  Without programs like this, we run the risk of stagnation and falling behind the curve.

So did I make any money for the company today?  Maybe not, but we’ll be making money tomorrow.

What I quickly realized is that the church serves its members in the same way as many businesses by:

1. Segmenting their customers (parishioners)
2. Understanding the unique needs of each segment (group worship, study guides, life applications of Bible verses)
3. Targeting products and services to each segment (baptism, small group study, mission trips)
4. Moving the customers through the life cycle (“Explorers” to “Committed Christ Followers”)

This is not a new concept for churches; many articles (including one in The Economist) over the past few years have chronicled the tremendous growth that churches have experienced by adopting business principles, and I was keenly aware that my last church in Michigan had adopted a customer focus to help parishioners along their spiritual journey (through the life cycle).

He also mentioned that they previously thought they could open a new church (a “branch”) and provide standard content, and that people would flock to the church – sort of a “build it and they will come” mentality. But once they adopted a more “customer-focused” approach, they experienced far more growth than they ever imagined.

Many companies have already adopted a rigorous, customer-focused marketing strategy to attract and retain customers, and to continually provide them with relevant products and services. But many companies that I have worked with either have not or need to become smarter about incorporating knowledge of their customer base into product and marketing decisions. If my local church can do this, surely most companies can as well.

Here is a webcast that outlines the increases in conversion and ROI that companies can gain from employing a rigorous testing program for their online marketing efforts.

We quoted similar research in our paper on using Behavioral Economics to improve online marketing efforts.

Here are two updates to my earlier post on using online coupons to enhance customer relationships.

First, a WSJ article in which the author looks for online coupons for consumer staples and provides an excellent comparison of several available coupon websites. I found it interesting that the aggregation sites seem confusing to navigate and spotty in their selection, yet there is a $1 off coupon available from the front page of organicvalley.com. She mentions that consumers redeemed only about 1% of coupons issued in 2007. Although this a somewhat respectable response rate to a marketing campaign, it also illustrates that there is plenty of room for improvement in creating targeted coupon mailings to consumers.

Second, an article in PROMO Magazine that reveals that, while coupons are effective for driving sales, 70% of purchase decisions are made in the store, and in-store displays and samples can be just as influential. Anyone who knows me knows I am a huge fan of Costco, and I naturally started thinking about the samples they offer. At noon on a Saturday, the sample army is out in full force, offering tastes of frozen pizza or the newest hummus dip. Many people partake so they can skip lunch or keep the kids happy, but many (including myself) also end up buying the product they’ve tried. While Costco likely analyzes the lift they receive from offering these samples, I wonder how much time they spend understanding the behaviors and preferences of people who visit on different days of the week or times of day – e.g., if I visit on a Tuesday evening, I am probably looking for that night’s dinner and would be interested in entrées, whereas a Saturday noon visit is to stock up for the next few weeks and I would be more open to snack foods and beverages. In addition, why not analyze my past purchase behavior and send me offers for new or complementary products – or offer these products for sampling at times you know I (and consumers who behave like me) will be in the store for sampling, then send me targeted mail letting me know they will be there?

We think the use of online coupons deserves a harder look. Emailing your customers and prospects with newsletters, product updates, and coupons is certainly nothing new, but it’s now well-positioned for even greater success:

• Companies are getting good at it. After dabbling in techniques like SEM and direct email, firms have gotten better at driving profitable growth from these methods, and many are increasing their focus on online advertising as a cheaper way to spend their marketing dollars.
• Consumers want more of it. During these uncertain times, consumers plan to increase their use of coupons to save some money. Sending these options straight to their inbox or mobile phone accomplishes that goal and positions you as a preferred provider.
• Consumers who use it are attractive prospects. Compared with consumers who only use offline coupons, Forrester reports that users of online coupon tend to have higher incomes, shop online, like to try new products, and influence peers. Younger consumers also use coupons, and they can be a good avenue to get the word out about your product.
• More data is available to help you win at it. More firms sell marketing lists (or can help you run campaigns to get new lists), segmentation data helps you understand consumers’ preferences and desires, and syndicated data helps you understand purchase behavior. Combining this data gives you incredible insight into consumers to tailor unique marketing messages.

You don’t just want to throw promotion dollars at existing customers to give them discounts on things they were already going to buy; rather, you likely want to use those dollars to deliver positive returns and achieve business goals – such as acquiring new customers, increasing market share, or increasing wallet share. Doing this requires targeting offers to customers based on their stage of the customer life cycle:

1. Acquire. Coupons can be a good tool to help consumers overcome the risk associated with trying a new product; if a new product is cheaper than the one they normally use, the savings might be worth trying. You can use them to attract entirely new customers to your firm, or to get your existing customers to try a new product line. Targeting early adopters can also help generate buzz, as they will influence friends and family to buy the product as well.
2. Grow/Stimulate. Once you’ve acquired a customer, you want them to maintain or increase their purchases. Two ways of stimulating usage are encouraging them to try a different variety (e.g., color, size, flavor) or showing them new uses for the same product (e.g., using Q-tips for craft projects in addition to hygiene). In this stage, the focus should be on the marketing message, the coupon being used to help seal the deal and drive the customer to the store.
3. Manage. In this stage, your customers are steady-state users, and couponing may not be required to retain them. However, these consumers present a good opportunity to test new offers on an already loyal customer base and measure the response before using them on the general public. You might test them using different demographics, layout, or wording, perhaps even running controlled experiments to determine which of two offers is more effective. We’ve done some research on the use of Behavioral Economics to improve offer design, which might be helpful in performing this testing.
4. Reclaim. If customers reduce their consumption or begin to try competitors’ products, you can use targeted offers to reintroduce your product and retain them as customers. However, depending on their needs and your product pipeline, you may otherwise opt to move back to the beginning of the life cycle and acquire them as customers of another of your products.

This strategy requires a high level of customer insight to understand preferences and stages in the life cycle. You can gain this insight by applying segmentation schemes to your lists of customers and prospects, and by analyzing your customers’ history of purchases and coupon redemption. Applying a rigorous testing approach will help you identify the most effective offers for each customer and stage.

Applying this framework to understanding your customers and targeting coupons will deliver several benefits, including:

1. Strong ROI potential. Campaigns that are more effective and lower-cost, targeted at attractive customers, have a stronger potential to deliver a positive ROI.
2. Better data to analyze results. Results of online campaigns are easier to track and measure than traditional campaigns, particularly if your coupons lead customers to purchase from your own website. Analyzing results from campaigns that involve multiple partners may require a different approach, as Vishal outlined in his earlier post on trade promotions.
3. Better customer relationships. You can use the insight you’ve gained about your customers’ behaviors, preferences, and purchase history to continually develop targeted offers. This level of personalization will help you deliver the right offers to the right customers at the right time, and ensure that your promotion dollars are spent most effectively.

Note: This post has been adapted from my earlier post on Analytical Engine.

1. Not everyone will rate. People may read the ratings when shopping for an item, but they won’t always come back to rate. Unless a site offers an incentive for rating a product, a customer’s only real incentive for doing so is to talk about how much they love or hate it; moderates may be under-represented.
2. Ratings will be biased. People’s individual biases produce variances in ratings, even if strict guidelines (think about employee performance reviews) are presented. In addition, new raters tend to rate high. Their average ratings decrease over time as they rate more items, presumably because they are exposed to more items and have a better sense of an item’s value relative to alternatives.
3. Ratings are averaged, masking the underlying data. Because people often only rate items they feel strongly about (love it or hate it), and an average of those extreme ratings may not truly represent the actual sentiment surrounding a product. For example, a review of rankings on Amazon.com revealed that “the reviews for the majority of the products have an asymmetric bimodal distribution. For these products, the mean of the online product reviews does not necessarily reveal the product’s true quality, resulting in misleading conclusions about the product’s future success.” In addition, established products are at a disadvantage against new ones. Consider a product that has received five rankings, four “5s” and one “4,” giving it an average rating of 4.8. If a new product enters the space and receives one “5” rating, it will be ranked higher than the other simply because it has fewer ratings.
4. Ratings may be false. Take the case of the Whole Foods CEO who posted disparaging comments about a competitor on a message board while talking up his own company, later stating “Sometimes I simply played ‘devil’s advocate’ for the sheer fun of arguing.” Other visitors may post false comments to artificially affect the rating, and these are not always removed from the calculation.

As more products are marketed and sold online, feedback-based ranking systems are increasingly common components. Amazon and eBay were among the first to use visitor ratings to rank products and sellers, and in February, Yahoo launched its Buzz service, which asks readers to click on their favorite stories, then uses those ratings to determine the most popular articles on the web.

Why is this important? Because accurate product ratings help predict that product’s success, and higher product ratings lead to more sales – or, as Allen & Appelcline state, “the value of individual items (most frequently goods) rise or fall based upon the largely subjective judgment of individual users.” So what can you do to ensure the rating system on your own website accurately reflects your customers’ views and the value of your product?

We’ve seen some thought around using analytical techniques and Bayesian mathematics to create better product rankings. Some of the solutions explored include:

1. Adjusting ratings based on known biases. Since some people rate higher or lower than others, one approach is to assign users a “User Optimism” value based on their rating history, and adjust the product’s overall rating based on the raters’ optimism value. Another approach is to remove all ratings from people who have only rated 1 or 2 items, helping to eliminate new-rater optimism or “drive-by” fraud.
2. Weighting a product’s ratings based on the number of ratings received. When a product has a small number of ratings, these ratings should count less than those for a product rated many times. To achieve this, you can add a “magic value” into the algorithm that calculates a product’s average ratings. This “magic value” brings products with few ratings closer to the average ratings of all products, then reduces its effect as more ratings are received, allowing established products’ ratings to float freely and more closely reflect the average of its ratings.
3. Adjusting the algorithm to account for bimodal distributions. To account for products that only have ratings at the extremes, one approach is to use a dual-point estimation model to more accurately reflect customers’ views of the product and predict the product’s success.
4. Analyzing a customer’s rating history for fraud. Someone who rates several products on your site should have a predictable rating pattern. You can analyze individual customers’ accounts to identify and remove anomalies that might skew product ratings.
5. Encouraging customers to leave text-based feedback. When a person takes the time to write out a product review, and knows that her name will be attached to it, she generally does a better job in her rating. These reviews tend to be closer to the average than those without.

Although your customers’ product ratings may be imperfect, they can still yield insights and value with the application of a good set of analytical techniques.

Note: This post has been adapted from my earlier post on Analytical Engine.