Strategies on How to Understand your Audience Effectively

When it comes to marketing, almost nothing is more important than knowing your target audience. 

Understanding an audience is at the core of any brand’s growth. It’s what drives effective marketing strategies, increases brand equity, and ultimately improves a company’s bottom line.

But “understanding” isn’t a destination. It’s a journey. It’s a process of constant review, refinement, and readjustment. Without regularly revisiting its target audience, a brand’s performance will decline at worst or stagnate at best. 

Every journey toward understanding begins with defining a target audience.

A target audience is a group of customers or potential customers who want or need (or would want or need) your products or services. These people are most likely to seek out, engage with and ultimately purchase your offering.

Your target audience should be people who want to engage with your business, rather than the people your business wants to engage with. There should be a genuine benefit for the potential customers through engaging with your messaging or offers.

But what if I told you the marketers are missing some critical information on their consumers?

Let’s take a look at the biggest challenges marketers face in getting the data they need and discuss some solutions to the disconnection marketers are seeing with their audience. 

CHALLENGES MARKETERS ARE FACING

The following are some of the predominant hurdles that modern marketers face:

  • Accessing Data Across Platforms
    We already know that modern customers use many different channels and devices, and create a multitude of data points all the way. For, this means they need to access data from multiple points to get a full picture of a customer. No longer will one single data set provide a complete understanding. A marketer may be missing key details if they don’t have information from the right channel.
  • Identifying Customers Across Channels
    Once a marketer obtains data from across numerous channels, the primary hurdle is matching data from various data sources to a single customer to get a fuller understanding of that individual.
  • Mapping the Customer Journey
    Modern customers go through many different steps across many different devices before they finally make a purchase decision. They might see an ad on their smartphone web browser, later follow your brand on Twitter, search for a product on their tablet, and start shopping from their laptop.
  • Identifying New Potential Customers
    Having fragmented customer data increases your chances of missing out on new potential customers. You may misidentify a customer, causing you to think they are not a strong potential lead. However, you may only believe this because you are missing essential data. Their smartphone cookies might not indicate interest in your products, for example, but their laptop browser data still might. To fulfill your campaigns and grow your sales funnel, you will need a way to find new potential customers who might become brand loyalists in the future.
  • Maintaining a Consistent Customer Experience
    Fragmented data can also lead to incoherence. Having an incomplete understanding will cause your target marketing and personalization efforts to suffer. For example, if you do not realize that multiple identifiers represent the same person, you might reach out to them repeatedly with the same offer and send them a coupon for an item they already purchased. This can make your company seem unprofessional to the consumer and may annoy them, damaging your brand’s reputation.
  • Maintaining Privacy Marketers also need to uphold privacy standards while still using data to enhance their marketing and the experiences of customers. Luckily, even though you are identifying customers, identity resolution still enables you to maintain customer privacy. 
  • Maintaining Privacy Marketers also need to uphold privacy standards while still using data to enhance their marketing and the experiences of customers. Luckily, even though you are identifying customers, identity resolution still enables you to maintain customer privacy.  The challenges above are difficult to overcome because they’re actively developing as data privacy regulations tighten and unprecedented events that change consumer behavior continue.
  • Maintaining a Consistent Customer Experience
    Fragmented data can also lead to incoherence. Having an incomplete understanding will cause your target marketing and personalization efforts to suffer.

So, what can marketers do now?

How can Marketers Improve their Data Strategy?

Data to Inform Your Strategy

You know that you need data to build your strategy. But, if you’re unaware of how to best collect and use that data, the process can be a headache.

If you’re working with an incomplete dataset and therefore an incomplete picture of your audience, insights will be too flawed to do you much good. Or, if you’re collecting a massive amount of information with no organizational structure in sight— you’ll struggle to pull actionable insights, to begin with.

An Objective to Guide Your Strategy

Forming objectives for your data-driven marketing strategy will guide your data analysis. By understanding the audience you’re hoping to reach and the call-to-action you want them to respond to, you’ll understand your end goal. Then, you simply use the insights unveiled by your data to discover the best path to reach that goal.

Possible objectives could be:

  • Growing your Millennial audience.
  • Successfully launching a new vertical.
  • Exploring social network marketing for the first time.
  • Holding an event series in a specific geographic location.

Believe it or not— each of these efforts can be directly improved using data. For example, data can reveal the ways in which Millennials are already interacting with your brand allowing you to optimize those channels. Or, it can give you a direction on which to, therefore driving foot traffic to your event series.

However, the data you’ll focus on in those various scenarios will be drastically different. The key is outlining your objective ahead of time to know where to start.

 A Plan Analyzing and Applying Your Data

Once you’ve collected and cleaned your overall dataset and defined your objective, you can begin analyzing your data. 

As you’ve seen, examining your raw data will do little to inform your strategy. Use your data marketing objectives to build your strategy through the following steps:

  • Determine which demographics or common characteristics will best address your objective.
    This is a process of analysis, discovering where patterns exist within your database and applying them for action. Decide which characteristics would best inform, such as geographic location, age, buying history, communication preferences, or social network use.
  • Segment your data by those characteristics for easier action.
    Dive into your data to discover leads most likely to respond to your marketing campaign and determine how you can best communicate with them.
  • Put the insights unveiled by those groupings into action.
    There are a variety of ways you can put your data analysis to action, including but not limited to ad retargeting, dynamic advertising, paid search results, and even email and direct mail personalization.

Ongoing Analysis of The Strategy

The entire point of these strategies is to learn from the data and improve your marketing efforts. It’s essential that you have a strategy in place for analyzing the success of your campaign to continue doing so.

Pay close attention to those who responded to your campaign and those who didn’t. Were there any surprises, such as likely respondents ignoring the effort or unlikely respondents doing the opposite?

Dig deeper to examine why they responded (or didn’t). Do your non-responders or non-buyers share any common characteristics that correlate with their response behavior?

With this predictive analysis, you can identify buyer personas and expand the prospects of your campaigns going forward.

You need a plan for when things go off course. When the next unprecedented event or unexpected challenge arrives, will you have the data you need to adapt?