By Jack J. Phillips, PhD
Dr. Phillips began the "Booth Camp" column earlier in the year and has covered how to get the most out of your exhibit by focusing on your outcome measures: reaction, takeaways, visitor actions, and now, business impact. As we make it into the home stretch of measuring outcome, read what Dr. Phillips has to say about the most important measure.
The last column ended with the collection of data about visitor actions after they leave the booth. Business impact is the consequence of visitor action.
Impact is perhaps the most important measure for top executives. For most exhibits, the impact is the actual sales generated.
Because of the nature of this level of data, it is easily tracked in the system and easy to convert to monetary value (i.e., the profit margin). The most difficult challenge is to isolate the effects of the exhibit on the sales data. This is possible and can be accomplished in a credible way. Let's assume, for example, a sales cycle (the time from the contact at the exhibit to when sales are generated) is four months. This cycle time is our ideal follow-up time to determine our improvement in sales (four months). Let's also assume that monthly sales have increased 10% at the end of the fourth month, and the specific measure is the total sales for the products exhibited at the conference. The key question would be: How much of the 10% sales increase goes to the exhibit?
Usually other processes are in place to drive increases in sales during this same period. For example, suppose additional promotions, advertising, and market growth are in place. Four factors (the exhibit, another promotion, advertising, and market growth) have caused the 10%. Identifying these factors is our starting point.
While there are many ways to isolate the effects of the exhibit, the most feasible way for this to work in this setting is to obtain estimates from those who understand it best. This technique begins by determining who the most credible individual is to isolate the different factors on the sales data. Sometimes it is the booth visitor – the person who made the purchase decision. In other situations, it is the sales representative. Essentially, we ask those individuals to estimate the extent to which this decision was made because of the exhibit – what they uncovered, discovered, and learned at the exhibit. This information can be collected directly from the visitor, through a questionnaire, a telephone interview, a face-to-face interview, or a focus group. Because of the cost of interviews and focus groups, they are often not used, but can be more credible. A telephone call or questionnaire might be the most cost-effective approach.
This information is developed by first reminding the visitor that several factors were in place that could influence the purchase decision (the exhibit, the other promotion, the advertising, and the market growth). Then, they are asked to list any other factors that could have caused the particular purchase at this time. The customers may list product design, pricing changes, customer referrals, or other issues that might have made a difference. Given these factors, the client is asked to estimate the percent of the purchase decision related to the booth visit (zero to 100%). For most sales, this estimate is going to be low because of the many factors involved, and some of the other factors may carry a greater weight. Nevertheless, the total contribution from the exhibit can still be a sizable number because of the large number of booth visitors.
Because this is an estimate, an error adjustment is needed. We want to remove the error by asking the question, "What is the confidence in the estimate provided (using a scale of zero to 10%, where zero is no confidence and 100 is certainty)?" The estimate of contribution is multiplied by this confidence to adjust for (or remove) the error. Obviously, this confidence estimate will not be 100%. The closer to 100%, the more confident they are in the allocation of sales to the exhibit. The ADA example, presented in the next column, will illustrate this calculation.
Other measures are driven by the exhibit and are analyzed in a similar way. The important point is that if a measure is important enough to track, and is expected to be connected to the exhibit, we must isolate the effect of the exhibit on the measure. The next column will focus on the ROI calculation.
Jack J. Phillips, PhD, is a world-renowned expert on accountability, measurement, and evaluation. Phillips provides consulting services for Fortune 500 companies and major global organizations. The author and editor of more than 50 books, he conducts workshops and presents at conferences throughout the world. His expertise in measurement and evaluation is based on more than 27 years of corporate experience in the aerospace, textile, metals, construction metals, and banking industries. He is chairman of the ROI Institute, Inc., and can be reached at 205.678.8181 or by email at [email protected].