Using big data and predictive analytics are essential to product market growth in agribusiness and agricultural marketing.
“You must always be able to predict what’s next and then have the flexibility to evolve.” – Marc Benioff, CEO Salesforce.com
It all starts with truly getting to know our customers. We do that through the tried and true marketing methods of customer segmentation, development of buyer personas and mapping out our customers’ buyers’ journey. Most marketers today are able to compile that data into a customer relationship management (CRM) system, marketing automation platform, business intelligence tool or even a spreadsheet for analyzation. This technology enables us to go beyond lead scoring to make better use of behavioral data and other data points throughout the organization.
When properly compiled, big data becomes a key enabler for growth. We then supplement this internal data with external intelligence gathering to get the entire picture. For example, scouring data sources ranging from the web to location to weather to social channels.
Stacking multiple data points helps improve agrimarketing by providing deeper insight to what’s truly motivating customers and prospective buyers alike. Marketers can analyze big data to better understand who their buyers are, why they buy, and how they buy to improve offerings, delivery times and accelerate next generation product development.
Typically, an organization will have a cross-functional team of engineers, product managers, marketers and data analysts when developing a new product or evolving an existing product. Therefore, it’s important to get the right team together to filter and evaluate data. As you synthesize data you may find it to be a truly proactive approach to inspiring new ideas or identifying new product features, enhancements or extensions. Or it may be quite reactionary to fix product quality issues or keep up with the competition. It’s all about making sense of this massive amount of data and using that data to address unmet customer needs.
BIG DATA AND PREDICTIVE ANALYTICS
- Listen to your customers – Gather customer service feedback, mine social networks and any other online sources for relevant data on your products/services and brand that are exceeding, meeting or failing your customers’ needs. Then make sure to communicate and take action to find solutions to help meet those needs.
- Listen to your gut – Sometimes data can support an emotion that drives trust within your target audience. And data ultimately validates whether the decision was a good one. Just be careful to not predetermine the results to influence data one way or another.
- Be accountable – With access to data, we as marketers have an ethical responsibility to help ensure the privacy and integrity of the customer data we collect. They trust us with this data, so we need to make sure they know we’re protecting it.
Living and marketing in an era of data farming agribusiness allows opportunities to enhance, develop and promote products that are more in tune with customer demands. Big data is no longer a competitive advantage in the agribusiness industry; it is a competitive necessity. Product innovation and evolution are keys to your business success, and big data provides the wisdom you need to stay ahead of the curve.
How is your organization using big data to improve products and customer engagement? Check out how Elevation Marketing helped Agrium Advanced Technologies leverage data intelligence to develop and market new season fertilizer technology.