Big-data analytics has been described as a transformational technology on par with the printing press. By collecting and analyzing large sets of data from multiple sources, enterprises of all kinds are turning vast streams of information into valuable business intelligence. It’s a frontier that trade-show organizers are just beginning to explore, according to a new two-part study by the Center for Exhibition Industry Research (CEIR).
Use of Analytics Today by Business-to-Business Exhibition Organizers documents overall trends in the use of analytics, while The Roads Traveled to Data Driven Decision-Making provides 12 case studies of a diverse group of associations and for-profit companies. The studies’ findings are based on the responses of 307 exhibition and meetings executives who participated in an online survey conducted by CEIR in the fall of 2014.
While the survey found that most respondents (68 percent) are engaged in analytics or will engage within a year, nearly a third (32 percent) have no plans to do so. Moreover, two-thirds say they work with data sets of 100,000 or fewer records — a volume that’s understandable for events that typically happen once a year, but that falls far short of the definition of big data, which is a broad term that refers to data sets so large or complex that traditional data-processing applications are inadequate.
Given this, it’s not surprising to find that the large majority of respondents are using general software such as Excel and Access to manipulate data, as opposed to specialized analytics applications.
Indeed, a critical finding of the study is that show organizers do not have to work with large data sets and complex analytics tools in order to produce positive business results. “The concepts of big data and analytics can be stifling for exhibition organizers, but they don’t have to be,” said Brian Casey, president and CEO of CEIR. “As the study shows, it’s the effectiveness of the analytics, however simple or complex, that really makes a difference, not the volume of data being analyzed.”
Other key findings and insights:
› The most popular uses of analytics are to support decision-making for attendee marketing (95 percent) and exhibitor sales (85 percent). These two areas are “low-hanging fruit,” according to the study, and the best places to start analytic efforts.
› Analytics are more likely to be “siloed” activities, supporting decisions for specific activities such as social-media campaigns or exhibitor-marketing programs. A minority of respondents is planning to link diverse data sets together to expand the range of analytics and the business objectives served.
› Roughly one-third of respondents use in-house analytic expertise, including IT and other internal staff, while one in 10 contracts out such work to consultants. More of the largest organizations — those with $25 million or more in annual revenue — have in-house analytic experts.
› Analytics are labor- and time-intensive, with one of the biggest challenges being “cleaning” data sets — detecting, correcting, or removing corrupt or inaccurate records — to ensure accuracy of findings.
› While a minority of leading organizations are experimenting with technologies like RFID (radio frequency identification) to obtain new kinds of data, most are not there yet.
› The study poses the question: “Will more generic analytic applications rise to the occasion, making their tools usable by generalists, or will function-specific applications [such as those used in event-management, social-media analytics, and CRM systems] step up their analytics offerings to remain the most practical and effective way for exhibition organizers to use analytics? Only time will tell.”
CASES IN POINT
The American Association of Diabetes Educators (AADE) is one of the 12 organizations whose data-analytics journey is profiled in the companion CEIR report. Gregg Lapin, CMP, who came onboard as AADE’s director of meeting services in 2014, immediately turned to a data-driven approach to address declining attendance and revenues at the organization’s Annual Meeting & Exhibition. No fancy analytics were involved: The outside strategic marketing company that AADE collaborated with for data processing used Excel with VBA (visual basics for applications), according to the CEIR profile.
“For us, it was mainly about analyzing data we already had, and putting together a strategy for implementing change,” Lapin told Convene. “For example, we had years of survey data telling us that that attendees found the cost of attending too high.” Among the many changes that AADE has made for its 2015 Annual Meeting in New Orleans: Attendee registration fees have been reduced by 42 percent, meeting dates were moved to fall over the weekend to take advantage of lower hotel rates, and better rates were negotiated at hotels within the convention block. So far, registration for the 2015 meeting is trending twice as high as during the same period last year.
Data analytics doesn’t have to be rocket science, Lapin said. And don’t collect information that has no value. “Only ask a question if you’re going to make a change based on the answer,” Lapin said. “Otherwise, why do you need that information? Asking the same questions year in and year out is a basic mistake I think too many organizations make.”
The analytics journey of the Auto Care Association is also profiled in the CEIR study.
Arlene Davis, CEM, CMP, vice president of meetings and events, said the key to success in her association’s case was targeting a specific metric for improvement and using findings from data analytics to build a comprehensive program — from promotion campaign to education content — around that. “We focused on one buyer segment, the owners of independent repair garages, and we ended up increasing their participation by 10 percent, our target goal,” Davis told Convene. With further data analysis and additional programming and target marketing, she said, the association is aiming for a 15- to 20-percent growth in the same sector at this year’s Automotive Aftermarket Products Expo (AAPEX).
“I think the terms ‘big data’ and ‘data analytics’ scare a lot of people away,” Davis said. “I’m telling you, don’t be afraid. Target, simplify, select. Then build everything around your target goal. This is exciting stuff.”