Unfortunately, organizations have been dependent on hardware-based, prohibitively expensive lead retrieval systems that have created barriers to purchase and adoption. Not only does this challenge deprive a company of having a successful exhibit strategy, but it also has left event organizers lacking robust data to take action.

The Problem with Weak Data

As organizations complete their pivot to omnichannel engagement, high-quality data is the foundation that supports an omnichannel approach. Data drives the content that an organization creates across their available channels to support an omnichannel engagement strategy. Organizations know that one source of content isn’t enough to satisfy all the different audiences that engage with an organization and use data to help guide their content. Essentially the better the data, the better an organization can engage with their audiences.

For an exhibiting organization, providing the right post-show content for all the people that they engage with at a tradeshow is key. Exhibitors need to capture as much data as possible from their interactions in the booth and digitize that data quickly enough to provide a prompt follow up using the proper channel. The success or failure of that follow up is impacted heavily by the complexity of their lead retrieval system.

Show organizers can also take advantage of exhibitor lead retrieval systems to get a glimpse into the exhibitor experience at a show. By turning that into actionable data, organizers can improve their show year over year and make changes directly to a show floor. But, the key to getting a complete picture is maximizing exhibitor adoption of the lead retrieval solution. The higher the adoption, the greater the visibility into exhibitor’s experiences – by creating barriers to exhibitor adoption, show organizers are limiting their own ability to take advantage of their lead retrieval solution.

Putting your Data to Work

The first step to acting on exhibitor lead data is to identify actionable pieces of data. Let’s start with the easiest two data points: high traffic vs. low traffic areas. By identifying the highest and lowest traffic areas on the show floor, show organizers gain a deeper understanding of what the most successful exhibitors are doing to drive traffic and how different activations help to increase traffic flows. Show organizers should ask themselves a few questions when looking at these pieces of data:

• How are my exhibitors driving traffic? They might be leveraging a high-touch activation, or they may have been particularly successful in pre-show promotions. Your exhibitor lead data can help you identify other data points that help contextualize your lead data results.
• Did we design any traffic drivers? A show floor is more than just booth space – food and beverage, demo areas and lounges are all places where attendees congregate during the show. Use these traffic drivers to help boost low-traffic areas and disperse attendees throughout the exhibit hall.
• How is the traffic flowing throughout the show? The entry and travel paths for attendees enables show organizers to learn about dispersal patterns among the show. These patterns help to identify where attendees are entering the show floor and how they maneuver once on the floor. Use this data in compliment with the two other questions to more effectively design high-traffic booth placements.

To collect the right data, place an emphasis on picking the right solution. Not only do you need a robust platform to collect this information, but you also need to select a solution that drives high adoption rates. Your exhibitor lead data is collected by your exhibitors – without a strong user base, the insights you can act upon will be limited.

The post Are You Making the Most of Your Exhibitor Lead Data? appeared first on Personify.

When I look at these numbers, I do not feel inspired to make a ton of resolutions. Yet, I continue to make them each year…and many times, I’m making the exact same resolution as the previous year.

Why do most of us fail at our resolutions?  

Unrealistic expectations play a big role. If I resolve to exercise five days a week in 2020 when I currently make it to the gym only a few times per month, I’m not setting myself up for success. And, when I fail this unrealistic expectation, it will likely make it harder for me to go to the gym altogether. 

If you’re creating new year’s resolutions for your personal or your professional life, make sure to set realistic expectations…ones that do not require an overhaul of your schedule and current processes or lifestyle. As with my approach to exercise, association and nonprofit staff can approach cleaning up their organization’s data with simple steps that break an overwhelming task into more manageable pieces.  

According to Dr. Marcelo Campos, a lectured at Harvard Medical School, it’s helpful to answer these five questions when creating and sticking to your New Year’s Resolution. Let’s apply these questions to the goal of eliminating dirty data in an organization…and keeping it that way: 

1. Why do you want to make the change? 

Dirty Data is everywhere. Forbes finds that 84% of CEOs are concerned about the quality of their data and Gartner measures the financial impact of poor data on businesses at an average of $9.7 million per year. It’s crucial that your team can trust and rely on your organization’s data. This is important from not only a compliance and regulatory standpoint, but also so that you can make data-driven decisions about the types of programs, events and activities that you should invest in to provide the most value to your members. 

Bad data can hurt an organization’s reputation, make you miss out on opportunities to engage members, and result in lower revenue when communication is not accurately aligned to the audience.  

2. Is your goal concrete and measurable? 

As we’ve already discussed, this is incredibly important. Ensure that you’ve put a goal in place that is both realistic and measurable. 

Consider how much time that you and your staff currently spend on ensuring that your data is accurate and is consistent across your systems and tools? Ideally, your AMS serves as the single source of truth for your organization and is synced with all other technology platforms regularly. If your making data hygiene a priority next year, be sure to account for the time that will be involved in keeping your data clean.  

Additionally, while clean data is a continuous goal rather than an item you can cross of your list, create a list of milestones and dates that help you confirm you’re making progress.  

3. What is your plan for dirty data? 

Now that you’ve committed to good data hygiene for 2020, it’s time to implement a plan of attack. There are generally three types of dirty data: 

• Inaccurate data: information that is out of date or was entered incorrectly 
• Inconsistent data: when data fields are missing or are formatted differently across records 

• Identical data: where a single contact has multiple records 

Your data hygiene plan should include steps to not only protect against all three types of dirty data but have scheduling times to routinely scrub your data and consolidate any duplicate records. Want to learn more? Check out our Data Hygiene Guide. 

4. Who can support you as you work toward change? 

Creating a data hygiene plan can be an overwhelming activity, especially when you have multiple years of dirty data to review and clean up. Create buy-in across departments and teams to help you fix bad data more efficiently and ensure it stays that way. 

There are a wealth of tools and resources that can extend your team’s limited resources. Look into an Integration Platform as a Service (iPaas) solution that allows your organization’s data to flow across systems as well as manage duplicates, create data filters and more. 

5. How will you celebrate your victories? 

Each time that you move closer to your goal of eliminating dirty data, take time to reflect on the experience and celebrate your success. This can be as simple as a shout out in your monthly team meeting where people share their recent wins and accomplishments. You can also bring in lunch for your team or plan an offsite activity when they finish surveying your membership and consolidating/updating all records in your AMS. 

Regardless of your journey, it’s important to remember that getting rid of dirty data is not a destination, but rather a journey of behavior change and regular maintenance. Be patient with yourself and your team, and don’t be surprised if there are setbacks.  

Are you ready to get started on your dirt data resolution? Well…you’re in luck.  

Watch This On-Demand Webinar 

The post Resolve to Clean Up Your Dirty Data in 2020 appeared first on Personify.