Event organisers are asset managers
Did you hear the one about the event organiser who became an asset manager?
It sometimes takes an outsider to see what you're missing. I talked with one of my marketing professors about the exhibition industry the other day. I confidently said trade shows were in the connections business, he said – confusingly – that they were in the asset management business. In this article I’ll share his perspective, and why I also now believe this, and explore how event organisers can use asset management principles to improve their shows. In addition, I'll discuss how to make this real and how one might get started.
This reframing may be very boring to exhibition organisers – if you think of an asset manager, my guess is you’ll picture a somewhat nerdy ‘finance type’ wearing a smart suit jacket who deals with stocks and bonds. This is far removed from the typical extraverted exhibition organiser. However, bear with me while I explain why a reframe helps, and the value of applying this new mindset.
Data as the new oil, and a real asset
Data was described as the new oil in a cover story by the Economist in 2017. If data is the new oil, then it may make sense to design businesses that create, refine, and analyze more oil/ data - i.e., if oil/ data is valuable, we should make more oil/ data. I've written about this in the past: there is significant value in using data to uncover patterns which help build better shows.
Another approach to treating data as the new oil suggests organisers should manage their data assets like an oil company. An oil company purchases an oil concession, then examines the area for oil. Upon discovery, they dig test wells and expand drilling capacity. Their investment spending is then shaped to maximize the long-term value of the oil in the ground. First and foremost, oil companies are asset managers. They decide where to play, and then maximize the value of their investments - sort of like launching and growing an exhibition.
Our usual association with asset management is with stocks and bonds - asset managers at say, JP Morgan, pick certain stocks to buy, sell or hold. Their toolset works in many other fields also. Asset management, according to Investopedia, is the process of buying, maintaining and trading investments that can grow over time to increase total wealth. Managing risk for a level of expected reward is often also included in the definition. Asset managers make decisions that shape what resources are held to create future returns.
Let's take an asset management approach to the exhibition industry. An organiser is in charge of launching (or acquiring), managing and divesting exhibitions with the goal of future growth.
This sounds easy, and it's what we actually do in practice without over-analysing. But what really makes an exhibition valuable? Organizers don't have fixed assets – they don't have concessions like oil companies, or complex machinery like manufacturers. Exhibitions are asset-light, low-barrier-to-entry businesses. Shows exist because someone identified an unmet need for people to meet on a topic and launched a show to fill that need. Exhibitions are almost exclusively made up of intangibles: the brand recognition of a show, the trust of exhibitors and attendees in receiving the value proposition - these are all intangible, all mostly unmeasurable, and the very source of value creation for an organiser.
Now, a successful exhibition is made up of a mesh of people, processes, and technology, but there's one thread tying everything together. In order to grow a show, you need to collect, refine, and apply data. It's about people, companies, interests, connections, and intent. Marketers segment their audiences with data. Sales reps leverage data to show deep knowledge of their industries. Exhibition directors use data to define their future growth direction. Owners use data to figure out where to invest next. Data is the red thread that drives the success of an organiser. Even with an excellent idea and a successful launch, growing becomes increasingly challenging and risky without a scalable data strategy.
Let’s think like asset managers
Turning to asset management, what if an organiser were to manage their data like an asset manager? If data is the thread that links the value creation of a show, by managing our data like an asset manager maybe we also create a situation where we end up running our shows like an asset manager.
If we think of a specific dataset as a data asset, we need to understand the return on acquiring this specific dataset (e.g. a list of potential attendees based on their affiliation or a technology improvement which allows you to monitor the interest of attendees at a show, etc). If it costs £x to acquire a dataset, what is the return that this asset generates over its useful life? Some data assets will be low cost to acquire (in terms of effort or expense), while other data assets may be very expensive. Taking an asset manager mindset to exhibition growth focuses on the output metric - the return on investment (ROI) - rather than the input metric - the “cost” of data acquisition. This is a fundamental mindset shift.
Some data assets have a direct relationship to value creation and are easy to measure. A new exhibitor creates a return for both the upcoming show, and for later years’ shows if they rebook. Using exhibitor churn and cohort retention, it is possible to place a value on an expected customer lifetime value; and hence understand the return on different routes to creating and converting data assets into sales. When evaluating exhibitors there are some further adjustments you may want to make, because different exhibitors create different levels of value compared to the price they pay. As an example, keystone exhibitors - established brands in their industry - are more valuable for attracting other exhibitors to a show. “Peanut sellers” who exhibit at a show for foot traffic alone, on the other hand, have lower value than the average, as they detract from the wider goal of a show being representative of their industry. Having a variable method of evaluating the value of an exhibitor creates a nuance that reflects the network dynamics of bringing an industry together.
Some data assets have an indirect relationship to value creation. The obvious group is show attendees, but there are other groups such as the media, speakers, influencers etc. These are all involved in the success of the show. A high value attendee to a show (such as a buyer from a large company) generates no cash value per se for the organiser, but their attendance is integral to the continued success of that show. Organisers spend significant amounts on marketing to attract these high value attendees (and the wider audience) - the data and effort that supports these marketing efforts has a cost. These individuals also have a value that can be calculated. There is a "shadow" price that could be calculated for an attendee. This shadow price is the price that exhibitors pay to access the audience, i.e., the revenue of a show. A simple division of revenue by the number of attendees gives the value of each attendee to the value proposition of the show. Without attendees there would be no exhibitors. There may be a need to adjust the "shadow" price for different value attendees, just as with exhibitors.
The above may appear very technical, but the benefit of being able to attribute revenue to value creation sources has some fundamentally powerful implications for a show organiser.
If you know the expected value of a specific exhibitor you can evaluate the effectiveness of different channels of exhibitor recruitment. For a given spend, which is the most effective? This can be used to evaluate additional sources of data, new sales and marketing techniques or new strategies for international sales - as well as understanding the current efficiency of existing channels and processes.
Along with working out what sales methods are the most effective, using an asset management approach means you can optimise spend and consider capital (re)allocation. Rather than relying upon a cost-plus budget each year, a data-led approach to value creation would help an organiser answer the question of when to continue to invest in something to grow the show, while the trend is hot, rather than dampen down the trend because there is limited sales and marketing budget remaining. By linking outcomes to spend, shows are more responsive and agile.
By placing "shadow" prices on attendees you can also start to understand the return on different marketing channels. This is more than just digital marketing attribution, it is a more holistic approach that understands which methods generate and retain the highest value audiences. To do this effectively there needs to be a way to triage attendees into various value categories early in the marketing funnel.
A detailed understanding of the clusters within exhibitors and attendees also allows a deeper insight into the linkages between them. I’ve written about how value is created by monetising cross-cluster connections at exhibitions before. An organiser can use data to understand the different customer ‘cores’ that exist within a show (and the wider industry), and measure how much interest (and value) each core has in terms of connectivity. With this data it is possible to invest in those “cores” that drive growth and therefore strengthen a show.
While the above may still be somewhat abstract, the reality is that an asset management approach moves an organiser to think in a more structured manner. This is because the ROI lens focuses the mind on the cost of customer acquisition, customer lifetime value, and a longer term approach to show health and growth.
So how would you do this in practice?
A 5-step approach lays out the way:
Perform a data audit, to determine what sources of data you have currently, and the methods by which data is created. The latter point is essential in understanding the flow of updated data into the business. Each source will have a different cost (financial and effort) and a different performance level. This can be a rough estimate, but it is necessary to understand the landscape.
Determine a baseline by analysing past financial data to understand the value of an exhibitor through time: what is the average value of a sale, what is the average retention by cohort. Then you can use this to estimate a customer lifetime value.
Segment exhibitors and attendees and other value-creating groups (speakers, influencers, press, etc.) into clusters that have similar characteristics. In many cases this may have already been done by manual classification and industry taxonomies. Where possible, seek to identify opportunities to automate this by building models which use data to automatically create clusters - as these can be used on both existing and newly collected data.
Define portfolio weights to allocate the baseline values to specific clusters. You want to work out the current value of these clusters and the marginal value of an additional member to these clusters.
Match the sources of data identified in the data audit to the specific clusters. Some sources may be general, and focus on many clusters, others may be more targeted. It may initially be hard to work out the value creation of different sources of data, however the process of starting to think in this way will likely lead to the tagging or labeling of data to enable proper evaluation of the value creation by different data sources.
If you have the skills in house to deploy such an approach, this is an excellent position to be in. If not, I’d love to help kickstart this process and do some of the analytical heavy lifting to help shows make more data-led decisions in where they allocate their resources in the most efficient way to drive growth.