Using Data Analytics – Where to Begin? How to Start?!

Using Data Analytics – Where to Begin? How to Start?!

Reprinted with permission from CAEM October Communique

Article Written by Jeff Tanner, Ph.D., Dean of the Strome College of Business, Old Dominion University
Nancy Drapeau, PRC, Research Director at the Center for Exhibition Industry Research (CEIR)

Take a deep breath. Relax. Ignore all the hype. You don’t have to have BIG data to make data-driven decisions.

True, the stories of self-weighing beer kegs that automatically issue purchase orders when empty or identifying which customers are pregnant by whether they buy larger jeans and vitamins sounds amazing but the data systems that make these kinds of Big Data applications possible aren’t commonplace in expositions.

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The reality is we’re in business-to-business and the data are different and not as readily available. So what makes sense for our industry?

The first thing is to focus on attendee marketing. Doesn’t matter who you are, that’s where the biggest gains are to be made. It’s also where you’re likely to have the most data.

The second thing is to recognize that this is the era of small markets. Every large market is made up of individuals, even when the customer is a company. When you are able to take the data you do have and segment more effectively, you can create relevant content (show floor offerings, educational offerings and more) that make sense for each of the small markets you’re trying to reach. And more importantly the messaging is more tailored to the individual; it will speak to them, which inevitably will increase engagement, response, attendance!

Use of analyticsWhat you can’t do is let the problems of data stop you. According to CEIR’s report Use of Analytics Today by Business-to-Business Exhibition Organizers, 32% of organizers are staying on the sidelines, not taking advantage of their data. That same CEIR report, though, does say that more than two-thirds of exhibition organizers are currently or soon to be actively engaging in data analytics.

There are three levels of data usage. The first is reporting, or using data to track activities or outcomes, for the purposes of monitoring activities or work processes. Examples might be exhibitor churn rates, attendance, and the like. The second level of usage is discovery, or analyzing data in order to generate new insights or understanding. Examples might be traditional marketing research to segment the market to develop target personas, using existing data to identify customer motivation or purchase patterns, and similar projects.

The final usage of data is production, or the use of data in real-time to identify customers and take appropriate actions. We call it production because models are put into production as part of the marketing process. In this application, models to decide what to do next in tandem with marketing automation, such as which email a potential attendee should receive based on what the attendee’s behavior has been on the website or dynamic scoring models that change how you respond to prospects based on what they do following a show or what offer they may receive to invite them to register to attend your event. Production models can seem complicated – but there’s a lot that can be gained just by using your reporting mechanisms and discovery opportunities more completely. You don’t have to be Google or Amazon to make the most of the data you have!

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The reality is that you can gain a lot with real-time monitoring, such as using location data (through RFID, Bluetooth, or Wi-Fi technology) to identify where a high value prospect is on the show floor and react accordingly. For example, perhaps an exhibit manager could text or email an invite to that prospect to stop by. Or perhaps real-time monitoring of conference attendee movement throughout the event is needed to confirm they are making their way to your exhibition floor – if not, then you could change your plans for inviting attendees more directly. Real-time monitoring by organizers can signal a need for tactics to make sure that the right actions are happening in-show to keep exhibitors satisfied. These sound like scary Big Data applications, but in reality, it’s fairly easy once you sign on to the technology.

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There may also be more data available to you now through the systems you already have. With some creative applications of analysis, you may be able to find new segments or micro-segments to reach with more relevant communications. For example, instead of segmenting by title, segment instead by previous session attendance, white paper downloads, and other content-driven data that signal interest by topic. Simple frequency analysis with a bar or pie chart created in Excel can help make these decisions.

So using Big Data principles is easier than you may have thought. But how do you begin to pull value from data?

  1. First, decide what business problem or problems you want to solve. Is it retention of exhibitors or increasing sponsorships? Or is it making attendee marketing or exhibit sales efforts more cost-effective, or attendee growth or targeted attendee engagement? Look for the low-hanging fruit, areas where an easy win can be had. CEIR’s report, Use of Analytics Today by Business-to-Business Exhibition Organizers, suggests that looking at ways to make marketing or sales more cost-effective is a good place to start.
  2. Get the right people involved. Buy-in from the top is very helpful – but insufficient. If you’re trying to make a decision about exhibitors, involve salespeople. Don’t forget someone from finance or accounting. They have data and, perhaps more important, insight that might accelerate the time to value.  Also, don’t forget to involve the keepers of the data at the outset. They know where your data is, in what format it is in and what it takes to have data ready for analysis.
  3. Identify what data is needed and see if you already have it.  The data keepers will know what you have and where it is but be sure to ask for data definitions. If you are combining data from different sources, you want to make sure that what is a customer in one data source is the same thing in the other data source or you need to come to agreement on what a ‘customer’ is for the analysis. In one instance, for example, a customer may be defined as an association member and in another, an attendee to a conference and trade show event and in another, a user of online education offerings. And these issues raise another, how do you make sure that one person’s activities are linked together into one record? If you are looking to better understand a customer’s relationship with your organization, linking such information is important. All these issues need help from the data keepers to assure the most useful and effective analyses.
  4. No access to a statistician? Then use analysis that makes sense to you.  Even simple bar charts or pie graphs provide a way to make sense of complicated data. Or consider acquiring visualization packages like Tableau that can add greater sophistication to those charts. Don’t forget, too, that professors who teach analytics at your local university are always looking for real projects for their students. If you can take the time, these are great resources.

If you want to take a deeper dive on this topic, several sources are available to you.

Analytics and Dynamic Customer Strategy (by JF Tanner Jr., Wiley, 2014) offers a road map for using data to inform customer strategy with many real world examples from small to the largest companies in the world.tanner

CEIR offers two documents offering a snapshot on the use of data analytics in the exhibition industry today; as well as 12 case studies revealing a range of uses of analytics by for-profit and not-for-profit exhibition organizers in different industry sectors.Use of analytics

Use of Analytics Today by
Business-to-Business Exhibition Organizers

data driven

Use of Analytics by Business-to-Business
Exhibition Organizers Case Studies


John F. (Jeff) Tanner Jr., Ph.D.

Dr. Tanner is Dean, Old Dominion University’s Strome College of Business in Norfolk, Virginia. Author or co-author of 15 books, his latest, Analytics & Dynamic Customer Strategy: Big Profits from Big Data (Wiley) was released late 2014 to wide acclaim. Dr. Tanner has taught executives and graduate students in a dozen countries, including India, France, Malawi, Australia, and Colombia, and recently spoke at E2MA’s Red Diamond Congress, National Retail Federation’s Big Show, Oracle’s OpenWorld, CRM Evolution, MSI’s Big Data Conference, and Teradata’s Marketing Festival.  Consulting clients include Cabela’s, EMC, and Procter & Gamble, among others. As a scholar, he has published 75 journal articles in such top journals as Journal of Marketing, Industrial Marketing Management, Journal of Education, and Psychological Bulletin and his research has been supported by grants from NIH, HHS, Walmart Foundation, CEIR, TSEA and others. In addition to research awards, he was the Society for Marketing Advances Distinguished Teacher (2013). Dr. Tanner sits on the boards of several corporations and non-profits. He and his wife, Karen, breed and race thoroughbred horses.

Nancy DrapeauNancy Drapeau, PRC, Director of Research, Center for Exhibition Industry Research (CEIR)

Ms. Drapeau is an admitted trade show junky and data geek. More than 15 of her 21 years as a market research professional have been spent in the business-to-business exhibition channel. She has had the privilege of serving as CEIR ‘s research director since 2011. She is a Nielsen Burke trained focus group moderator, holds a degree in Government from Georgetown University and a Masters from L’Institut Europeéns des Hautes Etudes Internationales.

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