How Agri-Tech Startup AgriWebb Makes Data Work For Them

Customer Spotlight: AgriWebb

AgriWebb is an Australia-based agricultural technology provider. Farmers use the company’s software to simplify farm record keeping and as it helps with audit and accreditation needs along with improving the productivity of their farms. The 40+ person company is growing fast and so are its data needs, with over 8,000,000 animals managed on their platform today.

Let’s dig in to see how data enhances this power-house agri-tech startup as we sit down with Brian Ritchie, Head of Growth at AgriWebb.

Tell me about you and your role at AgriWebb?

I’ve been at AgriWebb for one year and I was brought on to help marketing with organic leads and associated metrics.

We are a company that’s eager to serve farmers by improving their productivity using technology, which ultimately makes them more profitable. We want our software to be accessible and easy to use and that’s the mindset with which we started out our business.

The notion of starting a growth team within AgriWebb was that yes, we need to start marketing and we need to scale, but we need to do it in a smart, well-organized manner. When I came in, the engineering and product team were unbelievably talented - but they weren’t actively reviewing the business in a cross-functional manner. We had a good set of data that served us operationally. However, executive management and other key stakeholders both internally and externally did not have a 360° view of the company. For example - how does a specific campaign or ad messaging affect a cohort of farmers and change their behavior across the funnel? We never actively explored those questions before given the limitations at the time.

Upper management was investing in the company’s success and after my hire, we brought in a Sales Ops Manager and built a cross-company view of how the organization was generating revenue. We began to better understand our customers by answering questions such as, where do they come from and how do we connect the acquisition to the sale and subsequent onboarding - we wanted to stitch together the path from ad to farm paddock.

When I think about measurement in any new company - I typically start by recommending a data visualization and BI product like Chartio. This is because with their Advanced chart builder - we can easily expose the gaps in the data, especially when we’re blending multiple data sources and looking to hone in on a particular metric. Chartio while not as sophisticated as some of the more Enterprise targeted tools, is extremely robust for the early parts of the data maturity curve within an organization. We we able to link, flatten and cross-correlate various elements to build a comprehensive virtual data model to quickly analyze most of the information we need to drive business decisions.

With Chartio in place - it became more apparent we needed a unified data warehouse and that’s when we deployed Panoply.

With Panoply and its native integration with Chartio, I can combine product data, ad data and CRM data to paint a picture around our customers. We now have a very comprehensive view of our customer base.

Before, when we needed to provide the Board with an update on our company performance, our engineers would produce a CSV file by running a custom-built javascript with the required metrics numbers, such as the number of users, active users, companies, etc.

Today, we have dashboards that automatically let us slice and dice MRR and ACV (annual contract value) for a customer cohort, discover nuances of how customers are coming into and how these figures trend over time. We have much more flexibility and have moved rapidly along the ‘data maturity’ curve. We have four different structured plans and monthly/yearly pricing - and we can create different combinations of our offerings to yield the highest ACV before, during, and after a trial.

Tell me more about the data needs within AgriWebb.

For us, step one was getting our data together so we can describe our customer journey as described before. With the data warehouse infrastructure in place, we’re getting more mature as a data-driven organization, allowing us to start lead scoring in order to ensure we’re spending time on the best leads - based on the metrics such as churn risk scoring, engagement scoring, and conversion scoring from the point of exposure to our offering.

What data sources do you bring in to Panoply?

Every touch point, digital and non-digital that we have with customers. For acquisition, we track ad buys, media buys, click-stream data set. Specifically, we bring in:

AdTech : Google and Facebook Demand-Side Platforms

MarTech: Salesforce Pardot, AutopilotHQ, Mailchimp, Intercom, Aircall

Channel: Facebook, Twitter, LinkedIN, Instagram

Analytics: Segment, Google Analytics and Search Console, MixPanel

CRM: Salesforce

Finance: ChargeBee, Stripe, Xero

Product: MySQL, MongoDB, MSSQL, Amazon SES

What was life like before having a data stack?

Before I came in, we had no dedicated analytics infrastructure and a segmented view of the business performance. Frankly, we didn’t know what we didn’t know. Senior leadership relied upon pre-configured logic to generate charts and graphs that had static information and was not easily explorable.

Now, we can communicate what the logic, data, business definition of decisions and moves we are making.

What were your requirements when evaluating a data warehouse?

We needed a good data warehouse that had the integrations across platforms that we use in our day-to-day business. Secondly, we needed to be proactively given a view of our standing as a customer and how they’re working to make our jobs easier, faster and to do this for a competitive price. Lastly, we wanted a resource that could be queried across BI, Machine Learning and data visualization tools.

What has your big 'aha' moment been since adopting Panoply?

For us, getting a data warehouse in and itself was a necessary step, but for me, knowing that Panoply is working and doesn’t need maintenance was a big aha for me. Also, I love getting emails from Panoply’s customer team with news about new optimizations that saved me time on querying and storage space. I know Panoply won’t fail me and AgriWebb’s business operations will chug along with zero fuss.

What’s your favorite Panoply feature?

Materialized views are a very powerful mechanism that we haven’t fully realized the value of just yet, but as we mature on the data side, we’ll use it more. For us, the connectors and integrations both within Panoply’s UI and through 3rd Parties such as Blendo that seamlessly integrate with the Data Warehouse has been revolutionary…they just work. The ability to handle multiple schemas and dynamic data structures have been crucial to our business success.

Thanks for joining us, Brian!

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