Back to Blog

7 Considerations When Designing Data-Capable Marketing Campaigns

Last updated: January 29, 2020

analysts_ensureing_data_quality_jpg_vvz0_-Qt-1

Data is causing businesses to reevaluate how they operate – especially within their marketing department. In 2014, data driven businesses contributed $202 billion to the United States economy, proving the merits of data capable strategies. However, there’s even more potential in the world of data that has yet to be realized. A recent estimate predicted that 2.5 million terabytes of data are created every day, and this number is likely to continue to swell with time.

Unfortunately, marketers aren’t fully tapping into this potential, as 80 percent of marketers feel that data is being underutilized by their organization. That’s no surprise – decoding data to create data-capable campaigns and initiatives is a massive undertaking.

As a result, marketers must consider where to start when they’re architecting data-capable marketing campaigns. This requires putting a data-focused twist on your team’s targeting and goal-setting process, then ensuring you have all the necessary capabilities to ensure data quality across the entire data lifecycle.

Let’s take a look at seven considerations to make in order to create a data-capable marketing strategy.

1. Use Quality Data to Find the Right Audiences

The first step of any marketing strategy, data-capable or not, is identifying a need. However, data-capable strategies can be harnessed to find new audiences and new needs that a marketing team would not have thought of on their own.

With data, there’s no need to target customers based on instinct or historic results. Instead, marketers can collect and analyze recent customer data to find new ways to segment and target customers. Marketers can also build detailed customer personas that enable personalized marketing. This assists in customer acquisition as well as customer retention.

With product lifecycles shortening, it’s important for marketers to stay on the cutting edge of customer needs. Otherwise, your campaigns and product offerings will lag behind organizations that connect with customers in a personalized way, and offer the products that they want today.

2. Create Data-Driven Goals

Once the campaign has been oriented towards a need or desire, marketers should create goals that determine the campaign’s desired impact. For data-capable campaigns in particular, this is often done through SMART goals, which is a structured approach to goal setting. These goals must be Specific,  Measurable,  Attainable,  Relevant,  and  Timebound. For example, “By the end of the fiscal year, we would like to double our current conversion rate.” Then, marketers should analyze data that will gauge your progress towards these goals.

Then, support your determined goal by breaking it down into smaller KPIs. For instance, if an organization aimed to double their conversion rate, one KPI may be to increase their email open rates by 200 percent. Then, another KPI for the same goal may be to reduce webpage load times by 50 percent. This makes it easier to measure your progress towards a goal, and contextualize successes and shortcomings with data.

3. Enact Data Quality Standards from the Outset

Poor measurement creates poor data quality. So, marketers should focus on creating standardized processes that encourage accurate, holistic measurement across all of their campaigns. This is why 84 percent of leaders with successful data-driven marketing plans believe that defining data quality standards is the most critical process of a data quality initiative.

Enacting data quality standards can help you find data that doesn’t quite fit the mold. For example, marketers may want to find and control outliers, which prevents their data from being skewed away from reality. In addition to this, data standards can help your team identify, locate, and purge obsolete data from your data records, and further ensure that it’s not collected in the first place.

To assist in standardization, it’s common to create templates for routinely reported data. By filling out these templates, humans and programs alike can easily scan the data record to ensure completeness, and flag any areas that deviate from the norm. This helps your organization prevent erroneous conclusions.

4. Properly Manage and Organize Data

It’s important to have the right people, processes, and technology to manage and organize the data behind your data-capable campaigns. Organizations should build data governance policies that are intrinsically intertwined with their marketing processes. There must be ongoing monitoring to ensure that the policies stay tightly aligned to business objectives and processes related to planning, budgeting, and business alignment.

One way to simplify the management and organization of data is to create a data taxonomy – also referred to as “tagging” by some organizations. This works alongside your determined data standards, and assists in the integration of data into campaigns. A data taxonomy can be as simple as a table that spells out who manages the data, how often data is measured, any subchannels that are measured, and your current progress to KPIs.

5. Ensure Data is High Quality

High-quality data is absolutely essential to a data-capable marketing, as its central to the analysis of your customers and campaigns. It helps marketers perform basic data hygiene – this includes determining if they need to update customer information, manage duplicates, purge fraudulent traffic, and more.

It’s not realistic or necessary to attain perfect quality data. Instead, marketers should prioritize several key data quality dimensions, outlined in our report, Why Marketers Can’t Ignore Data Quality:

  • Timeliness
  • Completeness
  • Consistency
  • Relevance
  • Transparency
  • Accuracy
  • Representativeness

Marketers will enjoy a number of advantages as a result of adopting these seven data quality dimensions. This includes greater fulfillment towards KPIs like potential customer lifetime value, brand value, and overall operational efficiency.

6. Leverage Data for a Positive Customer Experience

A positive customer experience produces a range of benefits, like enhancing revenue, reducing costs, and improving a customer’s perception towards marketing messages. Historically, brands attempted to improve the customer experience through guesswork, listening to customer feedback, or mimicking their contemporaries.

However, data allows marketers to devise all-new ways to serve customers. With data analysis, your marketing team can find associations between mindsets within your target audience, and use this to create customer-focused segments. These segments will spell out exactly what a customer values when interacting with a brand, allowing you to engage with them in a more precisely targeted way.

While a change in the customer experience won’t happen overnight, it should be a top priority when designing a data-capable campaign. It’s been found that when marketers use high-quality data in their data-driven campaigns, they observed better customer lifetime value and benefits to brand awareness, value, and equity.

7. Facilitate Data-Capable Campaigns with Technology

Data-capable marketing campaigns rely on advanced analytics from the very beginning. As a result, it’s necessary that marketers have access to a marketing analytics platform that puts data quality first. This will allow you to not only find new directions for future campaigns, it will also allow your existing data-driven initiatives to scale.

By ensuring that your marketing team has access to the right analytical capabilities, your organization can track data across its entire lifecycle. With high quality data often being cited as the number one factor driving marketing success, data-capable campaigns must have this technology on its side. By doing so, your organization can enjoy successful data-capable campaigns that provide a competitive advantage in your market.

Written by Marketing Evolution