Transforming Trade Shows: Harnessing Data Science to Personalise Experiences
Updated: Oct 3
Do trade shows still matter? With the proliferation of innovative and high tech solutions, we need to ask the question if we aspire to leverage technology to deliver optimal experiences for participants.
Trade shows have been a cornerstone of marketing and networking in various industries for decades, facilitating face-to-face interactions that often result in fruitful business relationships and significant sales. However, the rise of digital technology and the constraints of recent global events have prompted a shift. This has brought about a host of benefits as well as challenges, the primary among them being the loss of face-to-face interaction that is so vital to these events. Here we aim to explore how we can use data science tools to personalise digital experiences, creating a compliment and sometimes substitute for face-to-face interactions at trade shows.
Reimagining Trade Shows: Physical Interactions, Digital Settings
The digital transformation bearing upon trade shows heralds a new era, marked by greater accessibility and expanded reach. There is the potential for a business from any corner of the globe to participate in a trade show without worrying about travel, accommodation, or setting up an elaborate physical booth. Imagining this democratisation of access creates a melting pot of diverse ideas and innovations, a feat that was difficult to achieve within the confines of physical locations.
Real-time personalisation at scale across a diverse array of digital activities can be a daunting task, often leading to a complex maze of metrics and goals that can confuse rather than clarify.
But challenges remain, for instance, how to reimagine face-to-face interactions. Physical trade shows have always thrived on the direct interaction between exhibitors and attendees. Conversations over products, impromptu meetings in corridors, and even the exchange of business cards — these seemingly small interactions often cultivate relationships that go beyond the duration of the trade show, yet their impact is rarely measured well to give us the data to better orchestrate these interactions.
We also struggle with the digital environment, where these interactions are no longer possible in their traditional forms. The extremes create pressure to design in an evidence-based way the optimal collision between these two extremes. How do we do it?
The Power of Personalisation: From Physical to Digital and Back
The answer lies in deep and real-time personalisation.
A one-size-fits-all approach is no longer sufficient. Attendees now have increased choice to consume a lot of what a trade show offers from their screens, where their paths are no longer dictated by physical layouts but by their interests and preferences. So, personalisation is about tailoring experiences for each participant with the objective of enhancing information exchange and satisfaction.
This trend is not just restricted to digital trade shows but reflects the broader demand for personalised digital experiences. A study by Epsilon revealed that 80% of consumers are more likely to do business with a company that offers personalised experiences, emphasising the significant impact personalisation has on engagement and satisfaction.
For too long the industry has looked to technology as a panacea for a fundamental product problem... data science is often used to tell businesses what they already know or suspect rather than being applied and empowered to solve a problem.
Achieving personalisation at scale requires a structured approach to 'productising' digital activities, breaking down complex offerings into distinct, manageable units. For instance, by defining a Commercially Valuable Outcome (CVO) for each ‘product’, businesses can align their efforts across different stakeholders and generate meaningful metrics that lead to more effective personalisation strategies. Doing so allows you to apply relevant data science tools to solve the puzzle of digital journeys, complimenting the physical experience.
We now have the tools to provide insights into user behaviour, track user paths, analyse session times, and reveal user preferences, allowing businesses to deliver tailored experiences. From AI-powered recommendation systems that suggest relevant exhibitors based on a participant's profile and past interactions to predictive analytics that forecast audience behaviour for the organiser, these tools play a crucial role in creating personalised experiences in digital trade shows.
The potential of data science extends beyond understanding participant behaviour. It must also enable event owners to measure the effectiveness of their personalisation strategies. Key metrics such as participant engagement, session duration, conversion rates, and online and onsite behaviour should be fed into models assessing whether personalised experiences resonate with the attendees to adjust strategies accordingly.
In the end, the objective of digital trade shows is not about replacing face-to-face interactions but leveraging technology to create engaging and personalised experiences that deliver lasting value to exhibitors and attendees. As we navigate the terrain of digitising trade shows, the power of personalisation, underpinned by robust data and analytics, aligned to the outcome of significantly increasing information exchange must serve as our guiding principle.
Deep Personalisation for Trade Shows
How do we operationalise real-time personalisation at scale as a strategy for trade shows? Implementing such a strategy across a diverse array of digital activities can be a daunting task, often leading to a complex maze of metrics and goals that can confuse rather than clarify.
We need an approach to break down the problem into distinct products, such as webinars, virtual booths, networking, physical stands, and seminars. This 'productisation' helps us view digital activities not as a homogenous mass but as a collection of unique experiences, each with its own goals and metrics. The approach fosters clarity and enables you to devise personalised strategies tailored to each product.
For instance, in an international trade expo held virtually and with hundreds of exhibitors and thousands of attendees, the organisers may want to provide a personalised experience for each participant, directing them to the most relevant connections which are not always exhibitors or sponsors.
Leveraging machine learning, you can analyse data from pre-event surveys and attendee profiles. You can also tap into behavioural analytics from GA4 in close to real-time to dynamically segment the participants into different groups based on interests and preferences. During the event, different sets of real-time analytics feed more information into the recommendation engine to continually adapt and augment the experience tuned to the outcome of maximising the IAEK Impact.
The heart of trade shows, whether physical or digital, will always be the interactions they foster – between businesses and customers, between peers and participants, and between ideas and opportunities.
By integrating these insights, organisers can provide real-time personalised recommendations to attendees, guiding them to relevant sessions and exhibitors. Post-event analysis shows attendees who follow these recommendations report a more satisfactory and rewarding experience.
We can no longer look at the problem of delivering Digitised Events as the act of bolting together as many features and functions as possible. Rather we must clearly identify CVOs aligned to engagement to help guide effort. This allows us to align efforts across many disciplines tuned to maximising the participant experience.
Digitising B2B Events - Personalised Experiences at Trade Shows
Why should we bother when audiences are up and back, and we seem to have COVID amnesia? Data shows that the present situation could be more buoyant. Evidence-based companies seek more RoI and audiences for better RoT (Return on Time). The challenge, then, of how we digitise trade shows needs us to articulate a clear why.
Our ‘why’ could be that we as an industry, want to prove that the investment in Live Events is empirically worth the money spent. And we should recognise that answering this question is worth the effort alone. To get to this answer, we must invest in our event personalisation, data models, and data science.
It is our assertion that for too long, the industry has looked to technology as a panacea for a fundamental product problem — one of deep personalisation and assured RoI and RoT for each participant. To this end, data science is often used to tell businesses what they already know or suspect rather than being applied and empowered to solve a problem. The data science needed to digitise events is one which gives us predictive models for what is going to happen and generates prescriptive models for what should be done.
Data and analytics tools serve as the eyes and ears of businesses in the digital landscape. They collect, analyse, and interpret vast amounts of data, providing insights into participant behaviour, preferences, and needs. For instance, they can reveal which booths are likely to be the most visited (and this does not need a heat map), which webinars will be the most engaging, or which networking events will be the most successful. These insights can then be used to tailor the digital experiences of trade shows to the needs and preferences of all participants, boosting engagement and satisfaction.
The Future of Trade Shows: Physical and Digitised Experiences
As we look towards the future, the landscape of trade shows will continue to evolve, with technology playing a central role. What began as a quest to replace face-to-face interactions has now morphed into creating distinct, exciting, and personalised digital experiences that complement and enhance our events. In this endeavour, comprehensive data and analytics tools, guided by approaches such as the CVI+CVO Framework™, serve as essential navigational aids.
Advancements in artificial intelligence, virtual reality, and machine learning promise to revolutionise the way businesses approach personalisation. Imagine attending a trade show where AI-powered systems curate a personalised itinerary based on your interests, virtual reality enables you to immerse yourself in product demonstrations, and machine learning algorithms enhance your experience in real-time based on your interactions. This vision of trade shows offers a tantalising glimpse into the potential of digital experiences.
While it's crucial to acknowledge the transformative potential of these technologies, it's equally important to note that they are merely tools to enhance human connection. The heart of trade shows, whether physical or digital, will always be the interactions they foster – between businesses and customers, between peers and participants, and between ideas and opportunities. In other words, information exchange.
In the end, the digital transformation of trade shows is not about replacing face-to-face interactions or even about personalisation. It's about harnessing the power of technology to create experiences that resonate on a human level. It's about cultivating connections, sparking conversations, and fostering relationships, regardless of the medium. And as we look to the future, the guiding principle should not just be about creating a digital replica of physical trade shows but about imagining what trade shows can be in this digital age.
The future of trade shows is ripe with potential, a canvas on which we can paint experiences that transcend geographical boundaries, break down barriers, and truly connect on a personal level. In the face of this exciting evolution, one thing remains certain: the power of connection and the human touch will continue to be at the heart of trade shows, physical or digital.