Today enterprises are plagued by the massive amounts of customer data stuck in departmental and technological silos across the organization, which hinders their ability to build complete customer personas and provide relevant, personalized experiences, writes, Sav Khetan, VP of Product at Tealium.

In recent years, the amount of data available to companies has exploded. Information streams in real-time via dozens of touchpoints, from mobile phones to in-store POS to smart TVs.

That rich data is an amazing opportunity for marketers. For years, they’ve been promised a 360-degree view of the customer that will enable the kind of relevant, personalized experiences customers want. Now, all that data is on hand — it just has to be assembled and orchestrated properly.

While marketers will be the biggest beneficiaries of a customer dataOpens a new window  foundation that enables personalization, they can’t go it alone. Customers don’t differentiate among interactions with marketing, customer service or sales — they have a relationship to the brand, not individual departments. An organization’s data foundation, therefore, must be similarly un-siloed. Put another way, marketers must treat customer data as a brand asset, not a marketing asset.

Learn More: Avoiding Death by a Thousand Cuts: Analyze Your CX Data, Keep Your CustomersOpens a new window

Assembling and leveraging that asset is easier said than done. Data from different channels arrive in different formats, tracking different variables. Before it can be used, it must be sorted, standardized and routed to the right places within an organization’s internal analytics systems. All this must happen within an independent, universal data layer that transcends departmental silos.

Building this complex infrastructure when your company is already ingesting enormous quantities of data can feel like trying to change a tire on a car that’s already in motion. But if it feels like a nearly impossible task, it’s also an incredibly important one. Only when all departments have access to a single, independent data layer can marketers begin to deliver the types of experiences customers want — and tap into the full value of customer data. This is why marketing must be on the front lines of the fight to break down silos and build a strong, scalable data foundation for the entire organization.

Here are a few guidelines marketing teams should keep in mind as they begin their data journey.

1. Even the Best Software Won’t Be Effective Without Good Data

This might sound obvious, but I’ve found that many people don’t understand just how critical good data is to the success of data-driven initiatives. Marketers tend to focus on software, thinking their problems will be solved if they plug in the right solution. However, all organizations run on a combination of legacy systems and contemporary systems, and usually legacy systems are the majority. Even if you complete every new software installation perfectly, you won’t fix most of your issues. Instead, with martech solutions, the old programmer’s adage “garbage in, garbage out” remains true. If your data isn’t standardized on the way in, you won’t receive quality results, no matter what software you’re running.

There’s only one way to ensure all your systems get good data: Build an independent, universal data layer that underpins not just the martech stack, but all stacks across the business. This will both standardize your data and make your data supply chain more robust since it won’t break every time you swap out a solution from your stack. With a strong data foundation, you’ll have the agility to assemble legacy and contemporary systems into meaningful solutions — and those systems will perform better since they’re getting better inputs.

It’s not just the quality of your data that matters, but also its quantity and diversity. Today’s state-of-the-art martech solutions are designed to ingest whatever datasets you throw at them — they don’t require specific inputs like older software does. So if you have more data to pour into the system, don’t hold back as long as your data foundation is in place.

2. You Should Plan Cross-Channel — Even If You Don’t Market That Way

Too often I see marketers build out data infrastructure for their immediate use cases without thinking ahead to what’s down the road. Don’t make this mistake. The true value of a data foundation lies in the full scope of its potential future applications, not the one way you happen to be using it today. You don’t want to limit your future self to data projects around just one use case or channel. Your infrastructure should be as flexible and scalable as possible so you can test new ideas immediately when they arise — instead of waiting weeks or months while IT builds out new infrastructure specific to your plan.

That need for scalability means your data foundation must be cross-channel and use-case-agnostic. Even if all your marketing programs, strategies and groups are organized at the channel level, the data layer should transcend all that, ensuring the same data is accessible across the entire marketing organization. If you approach the data foundation with this cross-channel mentality, it will bring true end-to-end visibility to all your marketing tools and create value across the company.

Learn More: 4 Identity Resolution Strategies to Drive Marketing

3. Data Readiness Isn’t Just the Responsibility of the Analytics Group

If a company wants to accomplish its data-driven goalsOpens a new window , it must make data readiness an organizational mindset. All groups should understand that they both consume and create customer data, and therefore share responsibility for building a strong data foundation. As stewards of a data-driven future, they must work together to ensure access across the organization.

Companies can build such a culture by educating employees on the value of good data and assigning responsibility for these initiatives within the organization. Data is more than a means to an end — it’s a singular asset that should be treated that way — and everyone should be on board with this mindset.

Realistic expectations are also an important part of data readiness. Marketers must align their expectations with the complexity of a given situation. Such changes often take longer than people expect due to the number of systems involved and the difficulty of getting them to work together. Be patient — good data is an investment, and like all good investments it takes some time to mature.

While it’s possible to make progress on individual use cases or one-off initiatives, the greatest gains will only come from a more unified, cross-channel approach that builds a flexible, scalable data foundation for the long term. The data-driven future is waiting — if marketers will step up to help build it.