Angela Smith is head of global events and field marketing for Atlassian. A pioneer in event intelligence, Angie leads a 20+person department that handles more than 600 events a year. She champions data-driven strategies that maximize event ROI, agile processes to manage constant change and replicable practices that improve event efficiency and scalability. Angie served as CEMA Board Chairwoman in 2018.
Data-driven Insights Make the Business Case for Event Marketing
Hosting and exhibiting at events is a vital part of the marketing stack. It is also a big investment both in direct costs and staff time. If you don’t have visibility into the business impact your events deliver, it’s easy to err on either side of doing too many and getting questionable value or cutting back at the expense of potential client and revenue growth. The ability to show the value of events allows your team and the company to spend marketing dollars where it makes the most sense.
Today event marketers have the data, tools and expertise to demonstrate how events contribute to accelerating customer relationships and growing the lead pipeline. It hasn’t always been this way. Before we had the means to demonstrate attribution to sales, justifying our presence at events was based mostly on perceived value: the teams were busy, the booth looked great, and people loved the swag. Nice to know, but not a reason to do more events.
My journey to data-driven event marketing started with an “aha” moment I had earlier in my career. I ran a large global field meeting for a major tech company and one year, the leadership decided to cancel all of our events to cut costs. I realized I’d needed to find a way to prove the value of meetings or reinvent myself.
I chose to do the former, and while that decision has paid substantial dividends professionally, it was a tremendous challenge because I had to learn to build the data and analytics “machine” from the ground up. And even though I had gained expertise in building the machine at prior jobs, when I joined Atlassian it took two years to put the data capture process in place and two more to build the data analytics system and attribution models.
Today our models drive insights for both our proprietary events, which serve as our channel to engage existing customers, build brand loyalty and expand their use of our products, and our field marketing events which are 100 percent focused on lead generation and pipeline acceleration. We capture data at our proprietary conferences through beacon tracking, so we can follow customers without having to touch their badge. At our field events, we scan every person we talk to. All of the lead data is uploaded into the event campaign in our CRM system. There, we can track the number of times we touch that lead, the conversations we are having with them, and whether they visit us at other events.
Using this strategy, we can show the effect of those touchpoints on creating marketing qualified leads as well as if it is resulting in pipeline acceleration. We can demonstrate that events have helped influence and deepen customer relationships. We have thousands of conversations going on in the pipeline on any given day and we can show how an in-person meeting at an event brokered a series of conversations and helped accelerate consideration. We don’t take credit for the deal, but we can show that for similar types of sales, customers that attend events move through the funnel more quickly.
Having good models and the right analytics platform also allows us to reassess impact dynamically. Our attribution models typically use a 180-day cycle, so we can determine real value of a specific event in that timeframe. We also continually measure effectiveness, so we can shift focus and change our approach to future events based on the outcome and learnings from the one we just did. The system also lets us track relationships and conversations from events over longer time spans. This helps show attribution in extended sales cycles, such as digital transformation or cloud migration projects.
Our process is still somewhat decentralized, because we're still fairly early in developing these strategies and plans. My team has inherited multiple lead aggregation technologies and for now, we manage our own technology stack vs it being managed by a central IT function. We’ve dedicated one event technology expert to help streamline our stack, a data analyst to help aggregate the data and to build dashboards that help us visualize all of this to help present it to leadership in a meaningful way. This has helped build strong executive support. I haven't met a CMO yet who didn't want data to back up marketing decisions, and our insights have been key to determining how to allocate resources to get the best bang for our buck.
As event executives know all too well, companies are always trying to do more with less. Having good event data, attribution models and reporting dashboards can help ensure that “more” is the right event to be doing and “less” is an optimized way to do it. I’m proud of what we’ve accomplished at Atlassian and look forward to seeing our industry make strides in data-driven event marketing.