How to Discover the Customer Growth Possibilities Hidden Within Your Sales Data
Presented By Proagrica Introduction
The increasingly competitive marketplace facing Ag Retailers makes it critical for them to identify and act on any opportunity to better serve their existing customers. Ag Retailers can create a strategic business advantage by unlocking the value in the data they have on-hand, using it to improve decision-making for themselves and for their customers; this creates a win-win, helping all parties to grow and succeed. However, without the right tools and the right knowledge, creating mutually beneficial outcomes can be difficult to achieve.
Understanding the Data
A common concern for Ag Retailers today is that their data is being under-utilized or that it is not clear what data should be utilized at all. “Because data can be difficult to pull together and make sense of, it is quite often used reactively when a problem occurs. However, if organizations have access to up-to-date insights on an on-going basis then they can become proactive in their decision-making and strategic planning,” says Marie Kennedy, Senior Product Manager for Proagrcia.
To meet the needs of growers and achieve a true return on investment in leveraging new technologies, Ag Retailers should be focused on setting up meaningful data analysis programs. “There is so much data out there and now we have to learn how to use it,” says Scott Cogdill, Director of Agronomy Solutions for Proagrica. “The ag industry has been slow to gain insights out of data. It has been viewed as single-use information, which has prevented people from getting the full spectrum of value.”
With a clear understanding of what the data on-hand shows, Ag Retailers can gain key business insights and determine the best course of action in areas, such as:
- How to maximize resource and minimize work duplication
- How to identify product sales gaps and opportunities
- How to identify potential customer challenges based on aggregate data
- How to forecast sales and future ordering more accurately
- How to use data tracking to predict future buying patterns and improve ordering processes
With clear visibility into sales, product, and customer data, each of these data points helps improve decision-making, enhance the customer experience and unveil new growth opportunities.
The Advantage of Commercial Analytics
Establishing long-term strategies for maximizing data and building supportive partnerships can enhance the value of your analytics program over time. “The right system strips out the noise and the mess to surface actionable insights from clean, reliable data,” says Ms. Kennedy. “When dashboards are easy to use, multiple roles across the business can answer their own questions rather than having to rely on a handful of super-users. Rather than having to go to each system or instance individually and run multiple reports, the platform brings the data together and standardizes it, so all users have the same single source of truth.”
In order to turn commercial insights into revenue opportunities, any analytics solution must create visibility and enhance communication. “We know it is very difficult for Ag Retailers to gain new customers because of strong loyalty between growers and agronomists. Increasing spend per customer and ensuring each customer is spending the highest percentage of their overall expenditure with you as a retailer is a vital way to improve revenue and profitability,” says Ms. Kennedy. Additionally, beneficial data analytics programs will be able to identify when new customers make a purchase and help the Ag Retailer to nurture that relationship to create long-term clients.
Agribusiness industry leader, Proagrica, has a tool specifically designed to overcome these data challenges, while providing both business and customer visibility. Powered by Proagrica’s advanced data integration and engineering capabilities, Commercial Analytics extracts, combines, and standardizes existing data from Ag Retailers’ key systems, providing valuable insights in a practical way.
To deliver accurate, actionable information, Commercial Analytics relies on use case-focused modules in five areas of importance to Ag Retailers. These include:
- Customer insights
- Sales Team insights
- Sales insights
- Product positioning
- Pricing insights
By utilizing data from these critical areas, Commercial Analytics can support Ag Retailers by providing greater visibility into their customer needs, purchasing patterns and challenges. Taking this information and creating business strategies based on these insights now allows Ag Retailers to make data-driven decisions.
Ag Retailers utilizing Commercial Analytics are able to segment their customers by size and goals, allowing the Ag Retailer to create a customized, valuable service and sales plan. The Commercial Analytics system also provides a way to visualize and understand the trends and metrics around each customer, allowing the Ag Retailer to reduce customer churn and eliminate challenges before they arise. Additionally, Commercial Analytics makes it possible for Ag Retailers to cross-sell and up-sell based on customer needs and buying patterns. “Understanding your customer profile completely – segmentation, purchase frequency, customer churn – it will give you a clear picture of your net customer value, allow you to make strategic decisions and minimize risk,” says Ms. Kennedy.
Looking Ahead
The rapid pace of change in technology within agribusiness makes it critical for Ag Retailers to understand the tools available that can help them to maximize customer opportunities and relationships. Proactively seeking a better understanding of the customer and managing the insights gained through data analytics will be key business differentiators going forward.
In addition to putting these strategic platforms in place, forward-thinking Ag Retailers will recognize the importance of choosing the right partner to deliver on these crucial technology initiatives. Click here to learn more about Proagrica’s experience and expertise in helping Ag Retailers achieve their data and analytics objectives.