Data interested in .
• Infer the interests of nodes you have less data about based on their similarity to nodes you have lots of data about – this is a key part of building good recommendation systems .
Left : Matthias Tesi Baur candidates are “ marketers or finance analysts ”. He continues : “ If you pair these people with a developer with a background in ETL [ extract , transform , load – a data integration process ], you have a potent combination .”
Data enrichment – the key step In order to prepare data to be structured into these easy-toanalyse formats , ‘ data enrichment ’ is the key . When I asked Mark which was more important , collection of new data or enrichment of existing data , he was emphatic : “ Enriching your data is far more important .”
First , data analysts generally start with basic cleaning – removing duplicates and standardising fields (‘ software provider ’ or ‘ s / w provider ’), for example . Then , they are ready to enrich their data to add more context .
Mark tells me that Events Intelligence uses Large Language Models ( LLMs ) like OpenAI ’ s ChatGPT and Perplexity ’ s API to scrape the web for information . They ‘ boil the ocean ’ with language-based AI tools to gather information about companies , what they do , how they describe themselves and who they sell their products to .
In this way , Mark can turn a simple list of exhibitors into clusters of highly relevant companies within industry subsectors , based on information from their websites . With data tools , he can find out which people or companies are similar , or as he puts it , ‘ close together ’. LLMs enable Mark to review and classify thousands of datapoints with far greater speed and attention to detail than a human could .
The bigger and richer the dataset , the more the data analysis software will give back . With enough input , it will tell you where your clusters and subcommunities truly lie .
Bringing in the outliers At the AEO CEO Forum in 2022 , Mark spoke about data , explaining that , “ the mind likes order and wants to put things in boxes and categories .
“ People are either attendees or exhibitors , delegates or sponsors . You ’ re either in this category or that category . But the real world isn ’ t like that ... When you seek to classify things , the outlier cases are always a problem .”
With enriched data , companies can bring those outliers into the fold and make better , more complete use of their communities .
Upskill existing talent One of the most common responses Mark receives from organisers when singing the praises of data enrichment is : ‘ We ’ d have to bring in a specialist ’. According to Mark , this simply isn ’ t true . Most data scientists worth their salt would grow bored with the relatively simple requirements of an exhibition . Rather than hire an overqualified expert at vast expense , it ’ s much better , Mark says , to choose analytical minds within your business and train them .
“ Typically ,” he says , these
Reticence around AI and data AI , like data , is an area that the events industry is behind the curve on . Matthias Tesi Baur , former chairman of the Digital Innovation Committee at UFI , explains : “ Just look at the size of AI departments in industries like banking or automotive compared to ours . In many cases , we don ’ t even have dedicated AI departments and the work is done by good old digital departments .”
We should take cues from other industries , he says . “ The best way to make the most out of AI ’ s potential is to learn from best practices in other industries . The hotel booking or online lead generation platforms such as LinkedIn are good starting points .”
What ’ s more , we should make hay while the sun shines . “ Right now [ ChatGPT ] is the cheapest it will ever be ,” Mark says . “ Prices will skyrocket as soon as it is deployed on a mass scale .”
If Mark ’ s predictions are true , the clock is ticking for exhibition organisers . As more companies jump on the bandwagon and enrich their data , a rift may emerge between the tech-savvy few and the uninitiated . Not only will data-led companies run their events better , they will also breach the ceiling of how much events companies have typically been valued . A window is opening – to move beyond the category of ‘ events ’ and into the rarified sector of tech . To make this transition , companies need to get dataconscious – and fast . EW www . exhibitionworld . co . uk Issue 6 2024 15