As pioneers in the CBD industry, Charlotte’s Web products improve the quality of life for tens of thousands of customers every day. As one of the largest CBD companies in the US, they require fast, precise and actionable data to ensure their family of customers are supported. 

The problem: Siloed Data, Clunky Reporting, & Hindering Data Culture

Like any fast-paced, rapidly changing business, Charlotte’s Web was facing widespread challenges of siloed data, data management, data governance, and slow analysis done in Excel by a loosely defined “data gang”. With no central data warehouse, data could only be analyzed from one system at a time. PowerBI directly queried their production ERP database, and they were stuck with the limited reporting provided by their e-commerce platform. Plus, they found PowerBI to be too unstructured, so it was only used by a select few employees, and virtually none of those users trusted the data. 

As summed up by Darren Kuehne, Manager of Business Intelligence: “A minimum of 65% of the data gang’s time was spent managing data, not analyzing nor activating insights.” The net result wasn’t ideal for the business: the analysts were the most informed yet least empowered contributors to a disparate range of projects throughout the organization. “We had hours of data management that was done in Excel to produce simple charts for presentations and planning, and we weren’t enabled to lead progress in the organization, even though we could see heaps of business value in our data. Worse than that, the data gang had more manual maintenance of these reports than they could manage in a typical work week.”

When he started with Charlotte’s Web in 2019, Paul Lanham, CIO at Charlotte’s Web, immediately recognized that data management was weighing down capable analysts. And – worse – it was creating a critical hindrance to building an actionable data culture. He began a technology selection process to enable the data gang with Darren at the ship’s helm. 

As a seasoned CIO, Paul identified the need to leverage flexibility, scalability, and timeline of a SaaS for the business intelligence (BI) stack. Within weeks, Charlotte’s Web had a full BI stack selected and implementation was underway. Together Darren and Paul understood that the BI stack required specialized IT & Data Science skill sets to fully enable the enthusiastic data gang. They began building a BI team charged with leading the rapid change Charlotte’s Web needed to continue its rapid growth. Molly Pagden and Ayan Sarkar joined the team in Q4 2019 and quickly helped facilitate the foundational change in BI operations at the company. 

The Solution: Data Clymer, Instant Data Team, & Modernizing Data Stack

Enter Data Clymer, a full data stack innovation partner, focused on data culture transformation. With decades of experience building and designing data warehouse & BI solutions, they understand how governed data democratization can enable self-service analytics and ultimately change the way an organization thinks about data.

Data Clymer provided an “instant” data team that was up and running in a matter of days. The team was able to implement the entire E-commerce reporting & analytics solution with a full data stack using a Panoply data warehouse, Matillion ETL tool, and Looker business intelligence platform. And they did it before Darren hired a single analyst. “Being it was my first time standing up a reporting infrastructure, having Looker, Matillion, and Panoply experts from Data Clymer who could be sounding boards was pivotal. They greatly influenced the support we received from all the vendors and were able to implement a system that I wouldn’t have been remotely close to delivering myself.” 

The business rationale for the components of the data stack:

Why Panoply?

Panoply is a fully managed cloud data warehouse solution that comes with some built-in connectors. It is extremely simple to start using it – create an account, connect some data, and go. Without Panoply’s plug-and-play administration experience, Charlotte’s Web could not have hit it’s six-week requirement for launching the BI stack. Their data warehouse is well-supported, well-documented, and has scaled with the business.

Why Matillion?

There are numerous reasons that Matillion is an optimal ETL solution for Charlotte’s Web. For example, in the ERP database, the rowversion datatype was a requirement for interpreting the incremental key, but Panoply didn’t support the datatype. In addition to processing alternate datatypes, Matillion provides the ability to load only the data that was created or updated since the last ETL job run. The result: fresh data syncing with the data warehouse in record time. Load times decreased from six hours to one hour per run.

Matillion exerts complete control over the data ingestion and transformation logic, enabling some handy features, like “always on” tables for analysis. These end-user facing tables are always available and up-to-date, leveraging simple functions, like update, insert or delete. Performing a full truncate-and-reload of the table can result in queries having incomplete data if they hit the table as it’s being rebuilt, so data availability and accuracy have also improved as a result of using Matillion.

Why Looker?

Looker is a best-in-class fit for Charlotte’s Web because of of its capabilities for driving governed data democratization. Since KPI definitions stored in a single place using the LookML data modeling layer, everyone in the company is guaranteed to be using a consistent calculation. Looker is also significantly more user friendly than the previous BI tools Charlotte’s Web had used. One end user exclaimed during a training session “Looker is amazing – it’s like Tableau but for normal people.”

The team at Charlotte’s Web is succeeding with data by leveraging popular Looker features, from scheduling reports for email delivery to setting alerts when KPIs cross certain thresholds. Kuehne says, “Looker’s scheduling feature has bridged communication gaps that I’ve observed since I started in 2018.”

The Results: 25% Customer Acquisition Increase & Data Culture Change

Charlotte’s Web went from entirely siloed data and no BI stack to delivering reports to cross-functional stakeholders in six weeks. Since then, Data Clymer has collaborated with the new Charlotte’s Web Business Intelligence team to build out the rest of the central data warehouse and analytical data model. 

Now, the larger organization subsequently shifted their relationship with data, what we at Data Clymer call data culture transformation. With the new data gang – lovingly called the Data Docs – they’ve been able to achieve multiple micro-wins that add up to a more efficient data culture:

  1. A scheduled Data ER (office hours to address complex questions)
  2. Slack channel to facilitate collaboration
  3. Cadenced Business Review meetings where stakeholders and the Data Docs sync on actionability of data and insights
  4. Ad hoc meetings to ensure new stakeholders who join the Charlotte’s Web team are able to access the data they need for success. 

Now, Charlotte’s Web leaders in eCommerce, Marketing, Sales, Operations, and IT have stable, consistent, and distributed access to the same data. This data culture at Charlotte’s Web supported the business when it had to pivot with agility in the Covid era. Due to brick-and-mortar stores being shuttered, the E-commerce business needed to increase output without significantly increasing headcount. The results from the company’s Q2 2020 earnings report illuminate the collective results of the win: “Strong DTC sales largely offset a 54.5% decrease in B2B retail sales which accounted for 28.2% of total revenue in the quarter. DTC net sales grew by 33.6% year-over-year as online traffic and high conversion rates increased through ongoing marketing and social media programs. Year-over-year new consumer acquisitions increased 25% and conversion rates increased 77%. DTC net revenue accounted for 71.8% of total revenue in the second quarter compared to 46.4% for the same period in the prior year.”

Data Clymer is a premier consulting firm specializing in full-stack analytics and data culture transformation. Our proven methodology includes full data stack implementation, data democratization, custom training, and analytics to enable data-driven decisions across the organization. We have curated a set of best practices from our deep expertise in LookerTableauSnowflakeRedshiftBigQueryPanoplyMatillonDBT, Sigma, and Fivetran.

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