Last week Stack Moxie and Dawit Tesfaye, AvePoint’s Director of Marketing, hosted a webinar about how AvePoint uses testing automation from Stack Moxie to scale its business and build out its new MarTech department. AvePoint is Microsoft 365’s largest data management provider, offering a full suite of SaaS tools to help companies with their own data needs. A five-time winner of Microsoft’s Partner of the Year Award, AvePoint has been providing data solutions to organizations for two decades. Dawit joined the company in 2019 and is now responsible for building out its MarTech department, which aims to lead the company’s digital transformation by centralizing its systems and identifying and fixing errors that lead to incomplete or inaccurate data.
In addition to this recap of the main points Dawit touched on, you can also find the full webinar recording here.
Why Does Data Matter?
When it comes to conversations about the role data plays in a company reaching its revenue goals, there’s no question that it can make or break sales and marketing’s efforts. While a lot of focus is on bad data and how detrimental it is to organizational success, Dawit emphasizes that the real focus should be on its root causes. It’s no use simply knowing that the data you’re using is inaccurate if you don’t know what created the issue. Furthermore, finding tools and technologies that can help automate and scale the process of identifying underlying problems is an essential step in growing out of chronically unclean data.
For a company like AvePoint, data is the most powerful tool they have to secure new clients and provide a reliable product. As a B2B company, the sales cycle is longer and involves more people than in a B2C environment, with each individual fulfilling a different purpose and role. Therefore, each of their data points needs to be accurately captured in order to efficiently target prospects and provide what they need.
Where are the Gaps in our Marketing Technology?
When Dawit and his team evaluated AvePoint’s current marketing environment, they identified the roadblocks that made it difficult to deliver correct information without the heavy lifting of manual testing. Siloed data, multiple marketing channels, and fragmented data sources all contributed to more time needed to ensure accuracy. In particular, siloed data and incorrectly set up attributions prevented them from the solid data foundation they needed. Data that was not easily accessible among platforms and groups made it unusable. Repeated use of band-aid and point solutions led to a MarTech stack that was difficult to manage due tof the number of tools involved to keep things running.
A Framework for Success
After analyzing the gaps plaguing the team’s process, the solutions for each issue could be summarized by one principle: Quality Assurance. Three main points served as the foundation of its execution:
- Data Collection: The ability to acquire and house more data points from users to enhance segmentation and personalization, ultimately leading to resolving all user actions into profiles.
- Data Integrity/Quality: The need to be able to standardize data collection across channels and platforms. By aligning all teams on which data points are collected, they can quickly create a single source of truth for customer data.
- Data Activation: Aggregate CRM data with behavior and intent to better understand the customer journey and optimize for it. This data can then be fed back into multiple platforms for strategic targeting.
All three pillars enable AvePoint to serve both prospects and customers better, leading to an improved customer experience. The framework used to provide solutions to gaps highlighted how important Quality Assurance was to success:
- Connect customer data from every first-party touchpoint to all the tools that need it.
- Ensure data is consistent, accurate, and filtering to the correct locations.
- Unify user history into comprehensive profiles and surface signals about each customer.
- Respect user privacy and stay compliant with regulations like the GDPR & CCPA.
At the center of these objectives, the implementation of automated processes that can keep data clean at the source is paramount to consistently reaching these set standards.
The Challenges of Manual Testing
Like many marketing teams, AvePoint devoted a lot of time to manually testing their data and platforms. Many marketers can understand from experience that this process was extremely tedious and time-consuming, and took resources away from other impactful projects. Testing involved filling out each form manually, following the data through each system, then downloading multiple CSV’s to cross-reference. The time spent on each issue averaged over 10 hours, making it difficult to handle efficiently. Scalability was also an issue that prevented the organization from growing past a certain threshold. Manual testing is not scalable because of the resources it requires, and multiple types of testing are needed to meet each of the MarTech team’s proposed objectives. It was clear that automated testing was a must in order to satisfy vital business operations.
How Stack Moxie Helps Quality Assurance
With Stack Moxie, Dawit and his team were able to tap into six main types of testing to help their QA efforts:
- Smoke Testing: Are integrations up and running?
- Real-time Monitoring: Do real leads perform as expected?
- Campaign Testing: Test campaigns before going live or after, to debug as needed.
- Standardization Testing: Are all data requirements met?
- Regression Analysis: Make sure new integrations don’t break old ones.
- Black Box Testing: Know what you don’t know.
The work that was done to identify gaps and areas to improve was a huge factor in helping them decide how to set up their testing in Stack Moxie. For instance, when they noticed that attributions were often inaccurately set up, especially involving LinkedIn,this gap became a focus for them when implementing Stack Moxie to provide solutions. As the backbone of BI and ROI analysis, automated testing could routinely check that valid UTM values were being passed from the correct sources and platforms and ensure proper attribution. Wrongly configured campaigns were also identified in Marketo, alerting AvePoint to another source of error in their attribution that would have been difficult to catch otherwise. Continuous monitoring of LinkedIn leads means they can prevent deeper issues from forming right from the start.
Overall, testing automation makes it possible to take control of data right from its source and constantly monitor each piece of a MarTech stack. This frees up time and resources to innovate and develop, which is impossible if each error needs 10 hours of manual attention.
We hope this information has given you a concrete example of how automated testing lets you advance your company objectives and improve your data.
Make sure to check out the webinar in its entirety for an even deeper look at how AvePoint is scaling its business and MarTech team with Stack Moxie.
To find out how your organization can use automated testing to achieve company objectives, set up a call with our team to learn more.