Strategy or execution: which is more important?
If you invest a lot of time in strategy with no execution, then your strategy won't get you anywhere. If you focus entirely on execution with no strategy, not only will your individual team members not have a clear goal for themselves, but everyone will be rowing in different directions.
The alignment of execution with strategy is important for all businesses who want to maximize their resources. But for agribusinesses—who operate in an industry that has sustained depressed commodity prices and negative external factors like weather and flooding—this alignment is critical to survival in a changing market.
When we look outside of ag, we see how businesses like Walmart, Target, Amazon and other major players in retail and other industries are achieving this alignment: through use of data. Virtually every major company, both B2B and B2C, has objective data on their customers’ demographics, buying behaviors, financial circumstances and much more. Plus, the biggest companies are employing artificial intelligence and predictive analytics to become better at providing the right product to the right customer at the right time.
Your agribusiness does not necessarily need to engage in this level of sophistication to be effective. However, having some relevant data on your customers can help you make better strategic decisions and better deploy your marketing and sales resources in execution.
In fact, data is the key component to achieving the balance between strategy and execution. Here are four reasons why that’s the case.
1. Data helps you create a strategy that's executable.
A vision tells you where to go. But a strategy will tell you how to get there.
Thus, a strategy without a plan to execute isn’t really a strategy.
Whether you are looking to expand your share of current markets, grow wallet share among your current customers, or look for opportunities to expand your footprint geographically or demographically, it is critical that your entire team can act on the strategy you build. This can happen in three ways:
- Anchor your strategy in reality & real-world insights
- Be realistic about what you can accomplish with your current personnel and resources
- Create a roadmap to revenue that takes the most efficient path possible
Data analysis is the key to anchoring your strategy in reality. However, much of the data that agribusinesses currently use either comes from aggregate USDA figures or survey-sourced data that runs into errors and does not provide the level of detail nor accuracy that agribusinesses need. This requires a source of data more accurate, detailed, comprehensive and current than what is traditionally used.
You won’t be going after all 2.8 million growers in the U.S. Not only is that an unmanageable number of prospects, but a significant portion of them are likely not going to be a good fit for your products or services:
- Not all of them can afford your product
- Not all of them need your product
- Not all of them are in a geography where you can deliver the product to them
Let’s say your business sells a premium hybrid corn seed exclusively in the Midwest. Your ideal customer is probably going to be a grower on a Corn/Soy rotation, located in the Midwest and is either an operator or owner/operator. You could then filter your market down further, looking at farmers who surpass a certain Gross Farm Income, farm acreage, spend potential for seed, and other key demographics.
MarketView is a tool from Farm Market iD that allows for this level of sophistication in audience-building.
Once you do this analysis, you will have a pretty clear idea of who your target growers are, their spend potential, and how many prospects you are available for you to go after.
2. Data helps integrate strategy with marketing and sales execution.
The data you need for the level of segmentation and detailed target that we demonstrated above won’t come from the USDA; not directly at least. It won’t come from a source that gives you name and address, plus some acreage estimates. It takes next-level data analysis to get next-level insights.
Here are some markers of data quality you will need for this level of analysis:
- The ability to aggregate grower-by-grower and field-by-field information, so your segments are accurate and precise, not estimates
- Clear pictures of how much land is associated with a particular grower
- Distinction between land owned versus land operated for differing use cases
- Ability to segment by acreage, crop type, geography, financial information, and more
In other words, you should start with detailed grower-by-grower profiles that aggregate to high level insights, not the other way around. That way, you know that your strategic decisions are based on highly accurate insights.
But there is an added benefit to this detail in your data. Not only does it give you better strategic insights, but that information can then seamlessly integrate strategy into marketing and sales execution. You can take your strategic target market and then turn that into lists of growers who can be exported for integration into digital marketing campaigns, or evaluated on a grower-by-grower basis for sales outreach.
Segment your target market into more specific and niche audiences for customized, contextual marketing outreach.
View detailed information on an individual grower to provide context for sales outreach.
In the end, data is the bridge that connects strategy to execution, making it a worthwhile investment to get the quality of data that helps your agribusiness.
3. Data helps you measure success against strategic goals.
It doesn’t matter how many marketing hits you get or how many sales calls you make, if you aren’t contributing to the business goals, it’s an unproductive use of time and financial resources.
For most agribusinesses, revenue growth is the number one priority, if for no other reason than that the company must continue to survive and thrive. However, revenue is a lagging indicator, so you have to keep track of other metrics as well:
- Audience reach among our target customers
- Prospect engagement level with digital content
- Conversion rates at every stage of the funnel
- Sales churn rate
- Opportunity to Close rate (large purchases, more B2B tactics)
- Website visit to purchase rate (small purchase, more B2C or eCommerce tactics)
If you’re basing your strategy on aggregate figures that may or may not encompass your ideal customer, you’ll probably set an unrealistic goal that demoralizes your team. If, on the other hand, you have a reasonable revenue goal based on an accurate picture of the market and the opportunities available to you, then these metrics should also be reasonable, and your team should be motivated to reach them.
There is, however, one quick qualification here. Sometimes, you don’t get everything right in the strategy phase. Maybe it’s bad data. Maybe the data is accurate, but you’re interpreting it incorrectly. Maybe you’ve been overly ambitious in how much to expect from your marketing and sales teams. Maybe you’ve been overly ambitious in how much your farmers are going to want to spend with you this year.
That’s why you not only have to base your analysis on data, but also the “boots-on-the-ground” insights you get from marketers and salespeople. You should never let data and analysis lead you to ignore the obvious realities that stand right in front of you.
If you learn something from salespeople that causes you to revisit your strategy, don’t hesitate to do so. Adapting and improving is always better than remaining static and failing.
4. Data empowers you to take baby steps...and let them snowball.
If all this data analysis and integrated alignment is new to you, it may seem a little overwhelming to think about how you’re going to execute and implement it with your team. That’s completely natural.
The goal is progress, not perfection. Take one baby step, like investing in some data to help you create more accurate strategic goals, helping marketers create more segmented campaigns, or enabling your salespeople with the information they need to have productive conversations with farmers.
Then evaluate how it worked. Did you feel more confident in your strategy because you knew you were basing it on reality? Did your marketers see better results due to a targeted, segmented campaign? Were your salespeople more prepared for their conversations going into the field, and did they leave the conversation with a farmer who is more likely to make a purchase?
Once you start incorporating data into one process, move on to another. And hold your team accountable for the correct use of the data in making their decisions and engaging in their strategy outreach.
The eventual goal is to take enough baby steps and earn enough small victories that it creates a snowball effect. This will not only help the business’ bottom line, but also the morale of your team. Eventually, you’ll build a culture of “we can do this”, with everyone riding high on the wave of the latest success and hungry for the next one.
Pretty soon, you’ll have a company that’s aligned around data-driven goals, knows exactly what the target is, knows how to reach that target, and is moving steadily toward it.