- Discussion & Discovery (Link to Step 1)
- Secondary Research (Link to Step 2)
- Clarify Objective (Link to Step 3)
- Primary Research (Link to Step 4)
- Strategy & Planning
- Implement & Launch
- Report & Benchmark
Having created and distributed our survey, the resulting analytics become our guide when creating a strategic plan of action. This step should be focused on accomplishing existing company goals by reviewing research findings and statistically supporting key decision making across all departments.
For more information regarding how we arrived at this point, we’ve provided links to previous steps above.
WHAT IS INCLUDED IN THIS STEP?
After reviewing our initial results analysis, we gather key department heads and stakeholders to discuss our detailed findings. Through this effort we identify areas in which our preconceived beliefs are confirmed or disproven. Furthermore, we establish areas in which cross-analysis of our data will provide a deeper understanding; pulling even more value from our data.
Equipped with our detailed study findings, we can create “buyer personas” to better communicate relevant information about our customers. These “buyer personas” are graphic representations intended to illustrate relevant attributes across varied consumer groups providing a better understanding of our customers; who they are, what they want, and how they differ.
With the breadth of results analytics, honing in on the most important data points can be a challenge. We consider which departments will be using the research findings, and then focus on data that provides relevant insights based on each department’s respective goals.
Now, we can reference a consistent data source allowing for strategic planning that is aligned across each department in support of our overall business goal; increasing revenue.
WHY IS THIS STEP IMPORTANT?
There’s a difference between producing interesting insights and actionable insights. The former can be thought provoking and spark discussion; however the latter offer guidance as we make key decisions and implement new processes.
Primary research data can create a proverbial “rabbit-hole” of data in which curious minds can get lost. If we lose sight of our ultimate business goal, the resulting analysis will not be actionable. By having open discussions with our department heads regarding our research findings we can help everyone understand the initial analysis and they can help us stay on track with what they need to accomplish their respective goals.
Through this collective understanding we identify and extract the most relevant insights, thus avoiding a tumble down the “rabbit-hole” of data. From here we create our “buyer personas” based on the most relevant customer attributes for distribution across any department looking to better understand our end user. Now, as we establish and develop our strategic plan, we can rely on accurate data to support our decisions rather than our individually biased perceptions.
For example, on one side our marketing department might be considering ideas for a new social media campaign. Segmenting results by age group will help them determine the best communication channel and messaging suited for each targeted consumer group.
On another side, our sales team might be planning next year’s revenue goals. Projecting units sold based on the wants and needs of specific consumer groups will help establish sales targets by individual product or service.
MACKENZIE BRANDED EXAMPLE:
By referencing previous steps in our project guide we remember our generalized project objective is “to better understand Athleisure consumers and identify similarities/differences within the daily lives of relevant customer segments.”
With the ultimate goal of delivering our marketing messages to these consumers with hopes of influencing their purchase decisions, we intend to leverage our results analytics to strategically plan our marketing content and channels of communication.
Having identified Millennial Females as our target consumer, data was collected from 18-34 year olds which is a relatively broad age range. While the overall data findings are interesting, we sought to uncover data findings that are actionable. To do so, we segmented our data by 18-24 and 25-34 year olds.
Through this detailed analysis we were able to dig deeper. While technically they are both within the millennial age bracket, we found some key differences to help produce more relevant, personalized marketing content.
|AGE 18 – 24
|AGE 25 – 34
|Spending ONLINE – $50-$149
|Spending INSTORE – $50-$149
|Organized Sports Participant
|Exercise 3-4 Times Per Week
In the table above, notice how the story evolves from looking at overall results to looking at results segmented by age group. We found some distinct differences in spending and lifestyle habits which identify younger millennials as a more attractive consumer group. As we continue to develop our sales and marketing strategy, we can reference these and other data sets to guide our marketing messages and content creation.
In an effort to make our data analytics a bit more palatable and easier to comprehend, we created two “buyer personas” to represent our two segmented age groups. To avoid an overwhelming data display we did not include all of our actionable insights, however this high-level perspective of our two main consumer groups will help the entire staff better understand our target consumers beyond the basic transaction.
Here are two examples of “buyer personas” based on our primary research findings. These have been distributed to our sales and marketing departments for strategic planning purposes. We’ve also shared these illustrations with the rest of our staff to help bring our consumers to life, and to illustrate the value of conducting primary research projects:
(CLICK IMAGE TO ENLARGE)
Be sure to check back soon as we continue our series with Step 6: Implement & Launch.
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