Crisp Acquires Both Lumidata and SetSight to Unify Retail Data, Enabling CPG Brand Growth with Target. Full announcement here.

February 23, 2024
Eliza Miller

What to expect from your enterprise data deployment

Crisp’s solutions consultant and data rockstar Eliza Miller shares the secret to seamless implementations that unlock retail data across the enterprise.

Enterprise CPG organizations generate a wealth of data from retail partners – but harnessing the full value of that data can be a challenge. Managing retail data pipelines internally requires vast resources and valuable insights can get buried under troubleshooting and maintenance demands. Average costs to build and maintain retail data connections can cost enterprise companies from $500k to $3 million annually, depending on their distribution size. 

With Crisp, brands can avoid these challenges with a dependable, automated retail software solution – but that’s not all. Crisp’s solutions consultants serve as guides that understand your unique objectives and can aid in maximizing your data’s potential.

Crisp Solutions Consultant Eliza Miller does just that. For years, she’s helped leading CPG brands unlock the power of their data, transforming raw information into real-time insights. Here, we’ll dive into Eliza’s approach to deploying Crisp solutions, and how she ensures vast amounts of data are cleaned, connected, and integrated into organizations’ existing systems for daily analysis and decision-making.

Enterprise expertise

Before Crisp, Eliza began her career as a Customer Success Manager, where she honed a client-centric approach to solution building. A draw toward a technical path led her to become a Data Analyst, where she soon found herself spending more time on data acquisition and cleanup than analysis. All too familiar with this pain point, it’s a key problem she now addresses for others at Crisp. 

At Crisp, Eliza’s weeks are a blend of strategic planning, implementation, and hands-on support. You can find her crafting tailored solutions and mapping out timelines, actively engaging with clients, troubleshooting issues, and collaborating with Crisp’s product team to incorporate helpful feedback. 

Crisp implementation and deployment

For each customer, Eliza crafts a seamless implementation plan to guarantee success based on each client’s unique needs and goals for leveraging retail data. 

It begins with collaborating with the sales team to gather specific needs and challenges the customer is facing. Eliza translates this information into a tailored project plan, followed by an in-depth onboarding session that delves deeper into organizational goals. Whether it’s a proof-of-value (POV) contract or a full-scale rollout, the process is approached with equal dedication, ensuring every client’s success.

During onboarding, Eliza engages with key team members across the Enterprise CPG organization. This might include someone from IT, who manages data governance; a Data Analyst, who will build and model reports with the data; a Sales team leader who directs initiatives based on data insights; and a Category Manager who will leverage Crisp data to inform broader product strategies.

Once onboarded, Eliza guides clients through three key steps to successful implementation:

  1. Retail data ingestion (1-2 weeks) This initial phase ingests a client’s data from major retailers (e.g., Walmart, Target, Amazon) into Crisp and typically includes two years of backfilled data. Eliza will review the data to make sure data is flowing smoothly into Crisp.

  2. Getting the data out of Crisp (30-minute call) – Next, Crisp will direct the flow of harmonized Crisp data to the destinations of the customers’ choice. These might include tools like Excel and Power BI or cloud destinations like Snowflake, Databricks, and Google Cloud. Because Enterprise companies typically have existing data infrastructure built with one or more of these, this data integration phase step is crucial – and with Crisp, the data is usually flowing within a day.

    At this point, Eliza suggests that clients look through their data to ensure high-level totals are correct and that all the products are present to start reporting on their data.

  3. Working with data in Crisp (ongoing) – Now, clients are interacting freely with their retail data within the Crisp platform. Eliza says that Enterprise clients will usually have a vision for their data and how they want to model it, and that’s why the integration step is so important. But it’s not unusual, she shares, for them to take inspiration from the Crisp dashboards for data modeling, or to even incorporate it into their workflow. For example, while analysts are working to model and analyze Crisp data in BI tools or the cloud, Crisp dashboards can provide informative, high-level reporting to teams across the company with a simple login.

Success is achieved when teams are effectively using the new feed of retail data to meet their stated business goals. This could include refining inventory allocation, adjusting product strategies, targeting marketing campaigns more strategically, or uncovering new market opportunities. 

To ensure Crisp continues to support the organization’s goals post-implementation, Eliza conducts check-ins and offers office hours, providing ample opportunity to assess progress, address challenges, and recalibrate strategies as necessary.

Solution success: ZURU Group

Eliza points out that a great example of a successful Crisp deployment is ZURU Group. When they came to Crisp, ZURU was a rapidly growing business facing challenges as its sales skyrocketed, driven by the popularity of its toy lines like Mini Brands, Snackles, and Pets Alive. But their existing data management systems failed to provide the real-time visibility needed to capitalize on their growing market presence.

Enter Eliza. She guided ZURU through Crisp’s deployment, quickly demonstrating its value, and leading to the team eagerly adopting more data integrations. Today, ZURU has evolved from siloed, manual data processes to a streamlined, automated flow of twelve retail data connections, including outbound integrations to Azure and AWS.

While ZURU deals in durable goods, Eliza emphasizes that data freshness is just as important to their success as it is for a perishable brand. Rapidly evolving toy trends, especially on platforms like TikTok and Youtube where the brand’s products thrive, demand it. By leveraging Crisp’s real-time data, ZURU has navigated sales trends and optimized inventory allocation, reducing markdowns by 50% last year.

By continuing to guide the team through Crisp’s capabilities, Eliza has not only helped propel ZURU to new heights but demonstrated the potential for other Enterprise CPG organizations to achieve success with retail data.

Future developments

Looking ahead, Eliza remains committed to assisting Enterprise clients in maximizing their retail data with Crisp. This includes supporting a growing interest in AI applications, such as utilizing Crisp’s clean, structured data for effective large language model (LLM) querying.

Eliza will continue taking customer feedback to heart, striving to deliver plans that optimize all facets of CPG business operations. What sets the company apart, and what she is most proud of, is Crisp’s exceptional responsiveness and its commitment to exceeding expectations.

To learn more about Crisp and the opportunity to work with dynamic Solutions Consultants like Eliza, book a demo here.

About Eliza Miller: Eliza resides in Washington DC, and outside of work she enjoys biking, running, and swimming; hoping to combine all three into a triathlon one day. Other interests include music festivals (loves funk and jazz), and a rekindled passion for WWE wrestling, which resurfaced as her favorite pandemic programming. 

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Be Data Ready for Anything

Crisp uses the power of the cloud to connect and analyze all of your data sources in real-time, providing you with the most meaningful insights and trends for your business. When you know exactly what’s in store, you can keep shelves stocked and customers happy while skyrocketing profitability.

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