How to Develop a Data-Driven Marketing Culture

Help your team develop the appropriate skills to win in the age of data-driven marketing.
June 10, 2021

Does your marketing department have a data culture? Ensuring that you have one is vital, because the gulf between those using data effectively and those using it poorly — or not at all — is only going to get wider.

There will be a sharp increase in the amount of data available to marketers as more digital channels and technologies emerge. Meanwhile, the disappearance of third-party cookies will significantly change the digital tracking landscape. Safari and iOS 14 already block them, with Google Chrome — the last browser standing — set to ditch them in 2022.

Third-party cookies allow marketers to build a complete picture of customers as they move from site to site. To deal with their disappearance, marketing departments will need to place greater emphasis on first-party data — information about what users looked at on their own website. But valuable first-party data often exists in silos spread across organizations.

Centralizing your organization’s data in a cloud data warehouse will greatly facilitate agile analytics and real-time marketing decisions. Yet HubSpot recently found that while 75 percent of marketers report on how their campaigns influence revenue, only 35 percent said that understanding return on investment is “very important” or “extremely important.” A recent Gartner survey found that nearly half of marketing decisions are made without the influence of analytics. One of the main reasons was resistance to implementing analytical recommendations that contradicted pre-existing plans.

So becoming a data-driven marketing department is both critical and difficult. It requires much more than investing in a swanky tool or reading up on the latest best practices. It’s a holistic effort that requires cultural and organizational shifts as well as an expanded portfolio of technology tools.

First: What Is Marketing Analytics?

Marketing analytics helps identify patterns within data to inform smarter decisions, and data-informed decisions about marketing activities drive higher efficiency and impact.

A data-driven marketing approach gives you a deeper understanding of where your customers are and where the market as a whole is going. It allows you to stop being reactive and start being proactive.

You can use data analytics to help answer strategic questions, such as:

  • Who are our customers and what do they care about?
  • Which marketing channels should we use to reach people?
  • What messaging and creative should we use to influence customer behavior?
  • How much money are we spending on acquiring new customers?
  • What should we do to increase customer retention?
  • What is our return on marketing investment across different channels?

For a more in-depth look at how to generate specific insights, check out our recent blog post “Seven Benefits of Marketing Analytics.”

Essential Building Blocks of a Data Culture

Data analytics is like a car engine, powering marketers on their journey toward better marketing outcomes. But an engine alone doesn’t make a car. Analytics must be supported by an organization-wide attitude that prioritizes data-driven thinking. In other words, organizations need a strong data culture.

Let’s take a look at five essential building blocks that will help you to win in the age of data-driven marketing:

  1. Define how a data-driven culture will help you achieve tangible organizational goals.
  2. Assess your data culture as things stand, identifying what needs to be improved before investing accordingly. For instance, if you struggle to understand your data, consider hiring a data scientist.
  3. Make this a top-down effort. Clearly communicate that creating a data-driven culture is a leadership priority.
  4. Ask managers to hold their team members accountable. Whenever a strategy changes or a new suggestion is tabled, ask employees to present the specific data that guided their decision-making.
  5. Champion data-driven initiatives. Celebrate wins, no matter how big or small, and discuss failures widely to understand what could be improved in the future.

But let’s go further. What else do you need to create a data culture in your organization?

Next Steps

1. Stamp Out Silos

Siloes cripple an organization’s ability to use its data effectively. You need to set up teams correctly in order to move confidently from initial insights to appropriate actions. Here’s how to do it.

  1. If you’re a growing organization looking to begin your analytics journey, hire generalists to start, and then invest in specialists later on. Generalists will get you up and running, but specialists will take you to the next level.
  2. Look to integrate dedicated data analysts into each team. This will allow them to serve each team’s specific needs, and they’ll be on hand to answer any ad hoc questions that your team might have.
  3. If this isn’t possible, consider putting your data analysts to use on a rotational basis, spending a day (or a week) at a time with different areas of the business.  

2. Facilitate Skills Development

Unfortunately, data-driven marketing isn’t as simple as purchasing analytics software and following precise instructions to the letter. Instead, you need to ensure that your team develops the appropriate skills to derive daily value from marketing data. Here’s how.

  1. Identify the skills that your team requires: analytical thinking, data visualization, software-specific skills (e.g., reporting in a BI tool like Tableau), and more.
  2. Score each individual marketer’s competencies in each of these areas. Consider using employee surveys to gauge individuals’ own perceptions of their analytics-based skills.
  3. Devise a skills development plan. Will you need to invest in appropriate learning and development tools? Is there any way you can collate experienced employees’ existing knowledge before sharing it with the rest of the team? How will you assess progress?
  4. Share this plan, including an estimated budget, with your leadership team for approval before executing.

3. Ensure You Have Accurate, Complete Marketing Data

Incomplete data gives you an incomplete picture of your customers. Without accurate, up-to-date data, your analytics efforts will be less than impactful at best. At a minimum, make sure to analyze data from the following six sources:

  1. Email marketing (aka marketing automation): Marketo, Mailchimp, HubSpot
  2. Customer relationship management (aka CRM): Salesforce, HubSpot
  3. Paid digital advertising: social media ads like Snapchat, Google Ads, LinkedIn Ads, Facebook Ads, Microsoft Ads, as well as ad delivery platforms like DV360 and AdRoll
  4. Organic social and digital: Facebook, Twitter, LinkedIn, Google Search Console
  5. Conversion data: Salesforce, Shopify, Square, Stripe
  6. Website or engagement analytics: Google Analytics, YouTube Analytics, Snowplow Analytics, Segment

Additional sources to consider: Qualtrics, Braze and Survey Monkey.

4. Implement a Modern Data Stack

Most marketers approach campaign or program analysis via an individual platform or dashboard. This can be helpful to see how a single campaign or element of that campaign is performing, but marketers often need to merge data from different sources to compare performance across platforms or bring together paid and organic efforts.

In the absence of automated technology, merging data may require downloading Excel files from multiple platforms — which can easily lead to human error, stale data, and ultimately burnout on the part of marketers trying to wrangle it all.

Rapid technological advances in cloud data tools mean you can now automate the process of extracting data from marketing sources and loading it into a single destination, where it can be used for analytics. This means automatically centralizing data from the platforms you use into a data warehouse, where you can query it. This is the only way to unlock reliable, useful and holistic analytics outcomes.

In short, marketers require a modern data stack. But what does this consist of?

  1. Data sources, such as Salesforce and Google Ads, to provide the raw data
  2. An automated data pipeline tool, such as Fivetran, to integrate disparate data into a single destination
  3. A cloud data warehouse, like Snowflake, to store all your data
  4. A business intelligence tool, such as Looker or Tableau, to enable data visualization

Marketers need to make better use of the data that’s available to them — instead of simply trying to acquire more. They need a sustainable, scalable system to move from raw and siloed data to valuable insights, and they need to minimize the number of manual steps involved in this process.

Marketers require a modern data stack powered by an automated data ingestion tool. A modern data stack empowers them to devote their time and energy to generating key data-driven insights — rather than dealing with manual data integration and broken data pipelines. It will also ensure they are on the right side of the widening gulf between truly data-driven marketing departments and those that don’t effectively leverage data.

If you need more guidance before you get started, head to our Marketing Analytics Resource Center. We’ve created an array of content resources — ebooks, case studies, videos, and more — to help marketers to develop a data-driven culture.

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