Marketing Communications

472 CHAPTER 14 EXHIBITIONS AND TRADE FAIRS

existing contacts, the spread over different product groups and direct and indirect budgets allocated. Based on

these limited data, the company built and tested an ROI calculation model based on the best available data and

accepted by the sales division, and easy to implement and maintain without any new software or systems. This

model was intended to allow for better decisions and planning with respect to the function of targets, budgets and,

based on ROI measurement, smaller and more focused stands, and the consideration of alternatives such as road

shows, master classes, webinars, better trade shows and events results, target-setting and show preparation, man-

agement and follow-up. The basic logic of this ROI model is given in the figure below.

Trade shows and events ROI model

At most trade shows, the three product types A, B and C are presented. They are shown on the horizontal axis. As

mentioned above, the average time between a first contact and a sale is on average six months for product A, nine months

for product B and twelve months for product C. This is also marked on the horizontal axis. The logic of the system

is that any effect a trade show can have would end after these time periods. However, the model allows for an ‘after

effect’ of an extra 20% of sales after these periods. All ‘after effects’ are assumed to end after one year. The ROI

measurement of trade show effectiveness is thus limited to a measurement cycle of 12 months. The vertical axis

shows which percentage of sales of each type of product that was realised after the show can be attributed to show

participation. Orders taken at the fair itself are not taken into account, because it is assumed that they are not the result

of trade show participation and buyers at the show had already decided to place an order before the start of the fair.

At the show, a number of leads are explored (e.g. business cards, sales conversations). For new customers, it is

assumed that 100% of these can be attributed to the fair. Based on previous experience and historical data, for

existing customers, it is assumed that only 75% of the new orders are fair-related. After 4–8 weeks, mainly depending

on the size of the fair, return on fair participation begins to be measured. A sale made to a new customer immediately

after this period is 100% attributed to fair participation. This percentage declines linearly as time goes by and, for

product A for example, only 20% is attributed to the fair after six months. Between six and twelve months, sales of

product A are linearly decreasingly attributed to the fair, until the percentage reaches zero after twelve months. The

same basic mechanism with different time intervals is used for the other two products, and for existing customers

(starting at 75%). The percentage of sales attributed to the fair decreases over time. The logic behind this is that,

as time passes after fair participation, the impact of other marketing efforts on sales becomes more important.

Finally, the total impact of the fair is calculated as a weighted average of sales in the period following fair participation.

The weights are the percentage for each point in time that can be found on the vertical axis. The impact of the fair

on sales is separately calculated for new and existing customers and for the three types of products.

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