BIG DATA in events

Ever increasing scores of companies are developing ways of – or are already longtime active in – offering their products and services online.  Companies are investing growing amounts of time and resources to online marketing strategies and campaigns to leverage customer loyalty and engagement in order to keep ahead of the competition.  Organizers of meetings and events are reluctantly slow adapting to the same practices.

One of the most important steps towards ultimate customer loyalty is in-depth, metrics based customer segmentation.  Going online with your company implies a larger, more international and heterogeneous customer base and thus more data.  But even for your real life event offer, you will need to know your customer better in the future, just to retain his/her attention and desire to participate.

Facing an explosion of available and collectible data on each individual customer, achieving solid segmentation becomes an even more challenging task.  So the question emerges, is big data worthwhile ?

Bit size data segments

To keep big data manageable, it’s considered to be good practice to breakdown the data.  Most client data collected online can be grouped in these categories :

  • contextual data : interests (identified and profiled), web pages visited, visited sponsors/exhibitors, …
  • attitudinal data : number of interactions, number of clicked ads or banners, number of visited pages,…
  • behavioral data : number of recurrent visits to your site, average visit duration, type of product bought,…
  • demographic data : age, sex, address, Facebook or Twitter id,…
  • loyalty data : number of complaints, number of recurring event visits, engagement score,…
  • value data : average amount spent on products, score for expected profitability,…
  • technical data : used operating system, used browser, Flash version,…
  • referral data : referral page, used search words,…

Breaking down the data into these categories has proven very effective to setting and achieving marketing goals.  Academic research has revealed that data segmentation supports the most important online marketing goals, such as increasing up- and cross-selling numbers, attracting new clients and improving churn rates.  The categories of attitudinal and behavioral data are well suited for supporting almost every goal, whereas demographic data is less effective, because of privacy restrictions prohibiting massive online collection of this type of data.  On top of that, although it’s usually the type of data that’s used when segmenting for events, it’s totally irrelevant towards target groups’ interests.

If after reading this part, you’re still wondering what big data is and how it distinguishes from regular data, then read my previous blog post (in Dutch).

Big data challenges

Companies are feeling overwhelmed with massive amounts of data and information.  So how do you manage that ?  Before this explosion occurred, companies were faced with less amounts of data and mostly structured, primarily disclosed in such applications as ERP (Entreprise Resource Planning) and CRM (Customer Relationship Management).  Today, together with the breakthrough of internet based platforms, not only the size of databases has increased tremendously, but also the complexity of the information.  Data can nowadays be stored in structured or unstructured ways, in video, audio and pictures, not just in text.  Managing this and turning it into valuable insights, requires new work methods.

Big data and traditional data not only vary in volume, structure and transaction speed, but also require new tools and technologies.  Today many data management techniques are used in big data that have a common background from the techniques used in traditional data : classification, clustering, regression, time series analysis and A/B testing, to name a few.  But Big Data demands new techniques that empower companies to store, process and analyse vast amounts of unstructured data originating from different sources in various types and sizes.  Big data also requires new and improved visualization methods and tools.  Ways to display all that collected data that are comprehensive for humans, so they can actually use it to make business decisions.

Is big data a joy or a burden ?

It’s a joy if you find the appropriate way to derive knowledge from the data.  Segmenting client data plays an important role in this game.  It will substantially contribute to making better and semi-automated decisions on marketing strategies and tactics to increase the customer engagement.

Start planning for big data today if you’re in the event industry.  There’s no way it will not impact your business in the future.  Big data is directly linked to the way your future customers behave today.  Look for my next blog post in which I will try to depict your John Doe customer of 2015.

Don’t take BIG DATA lightly or as a pure IT-problem and get expert help.


9 data management tips for events

Small or large companies in the event and meeting industry have to deal with data collected on their exhibitors, partners, sponsors and attendees.  Managing this data is far too often considered a pure IT-issue, solved by technical people when they install a database management software on some in-house or externally hosted server.  And then I won’t mention all those, even bigger companies, that just keep the data in separate Excel-files per edition of their event(s).

But obviously it’s not a technical IT problem, far from.  Managing data is supposed to help you get intelligence on your customers.  You need that intelligence to make clever and business accelerating decisions to improve your product offering and maintain your competitive edge and relevance in the market.  Equally, you will need that knowledge to cater for effective, 1-on-1, relevant, converting marketing campaigns.

Even without considering the data stream that comes from opening up the gates of internet and online platforms, event and meeting organizers typically already have to deal with rather large amounts of data.  Data on their prospects and customers when it comes to exhibitors, data on their prospects and customers when it comes to attendees or visitors, data on the products and services they deliver, financial data, transaction data of ticket sales, survey information, …

All of that data is constantly changing at accelerating speed.  So how do you manage that ?  Here’s 9 tips.

1. Make data management a priority

What many event organizers don’t realize today is that accurate data on vertical markets is their prime business asset.  That must be treated with care.  Make sure this data stays in top shape.  Do so by spreading quality awareness and appropriate measures and processes across all levels of your company.  Google is not about search, Facebook is not about distributing socially appealing messages and likes, they’re about providing relevant information and advertising to customers and delivering that back to their advertisers, all based on extensive data.  You as an event or meeting organizer are no different and can even be better at it if you have all the relevant data for your markets or special interest groups.  Hell, you could even start selling your data to the Googles and Facebooks of this world.

2. Procedures for quality

Develop strong and rigorously implemented and monitored procedures for handling data.  Disallow root access to all data for everyone in the company.  Implement the processes and rules in your data management software solution.  Install a role based access rights system.

3. Hire a data specialist

He/she is responsible for sourcing, buying, importing, exporting, enriching, deduplicating and analyzing data.  Marketing helps him/her, if required, with segmentation, finding potential sources of extra or new data.

4. Segment don’t separate

Exhibitors, sponsors, partners – gold, silver, bronze, whatever – visitors, attendees : they’re all customers, just with a different business value to you.  Some or many, depending on the case, will have multiple values for different event brands in your portfolio.  Don’t store them in separate databases based on their initial contact or business value.  That value might change over time.

5. Segment further

Figure out the customer information as detailed as possible.  Categorize potential exhibitors in a structured way on industry, product groups – standardized SIC, NACE but also your event specific products groups – company size, revenue size per product group, ABC-category, competitors per product group, main industry markets, focus geographical markets,…

For visitors segmentation go for interests, buying power and buying intention.  For B2B-events add company size.

Do regular data integrity checks on these segments.  Filter out all those addresses that have slipped in over time as incomplete, missing one of the segment information elements, and take the time to complete.  This information will prove valuable to you in sales and marketing efforts.

6. Develop buyer persona

From the segment information you can derive archetypes of visitors and exhibitors.  E.g. a male maintenance technician between 30-40 years old working in the chemical industry located in the Antwerp province.

For each of these archetypes try to answer these questions :

  • Priority Initiatives – What causes certain buyers to invest time in my event, and what is different about  buyers who are satisfied with the status quo and don’t attend?
  • Success Factors – What operational or personal results does your buyer persona expect to achieve by attending?
  • Perceived Barriers – What concerns cause your buyer to believe that your event is not their best option?
  • Buyer’s Journey – Who and what impacts your buyer when evaluating their options?
  • Decision Criteria – Which aspects of the competing options does your buyer perceive as most critical, and what are their expectations for each?

7. Test

Test your data all the time, newly acquired data and existing data.  Over 20% of personal data becomes inaccurate after 1 year.  And that percentage grows if you take into account product data, market data,…

Do A/B-testing on your data sets.  Test purchased or otherwise newly acquired data before importing it into your CRM-database.  Use the test results to score data providers or to develop a data quality game inside your company between product range departments.

8. Build a solid data warehouse solution

Externally or internally hosted, doesn’t matter, that’s up to the manpower and skills you have available, but always look for a solid, scalable, performing, secure data warehouse solution. Set it up including a test, staging and live environment.

9. Prepare for BIG DATA

While all of the above is SMALL DATA and already a big challenge to maintain well, you must play in the back of your head with the idea of going for BIG DATA.  It will, as in many other industries, and not long from now, be of the utmost importance to event organizers.  You will want to know everything there’s to know about your exhibitors and visitors.  This information will not be available to you in clear, structured packages, like SMALL DATA.  It will have to be processed at ultra-high speeds and the volume will be huge.  This is a true challenge but when executed correctly this data will give you the ultimate knowledge of your target groups and insights needed to keep your event top of mind.

BIG DATA may seem like an overwhelming and over-anticipated monster, but with the appropriate strategy and tools, professional guidance and continuous evaluation and adjustments, you will master this too.  Big data in events : a great topic for my next post(s).