12 Questions to Ask Before Your Next Data Project

A data project can look promising on paper. The right systems have been selected, the integrations have been mapped out, and everyone agrees that the business needs a better way to use its data.

But connecting data is only part of the job. Marketing, Sales, RevOps, and Digital teams also need to trust what they see, understand what it means, and know how to act on it.

These 12 questions can help your buying committee define what the project needs to accomplish, uncover gaps before they become expensive problems, and avoid building a data layer that creates more information without making it easier to use.

Define What the Project Needs to Accomplish

“Unify our data” sounds like a solid goal. The problem is that it can mean almost anything.

Before talking about platforms, integrations, or fields, get specific about what should change once the project is complete. What should teams understand more easily? What should they be able to do faster? Which problem is important enough to solve first?

Those answers will give the project direction and make it easier to decide what actually belongs in the first phase.

1. What decision or action should this data make easier?

Think about what someone should be able to do that is difficult today. Maybe Demand Generation needs to see which target accounts are showing renewed interest. Sales may need better context before reaching out. Marketing might want to adjust a digital experience based on recent behavior.

The more specific the answer, the more useful it becomes. “Give Marketing better data” leaves too much open to interpretation. “Help Demand Generation identify accounts returning to high-intent content” gives the team something real to plan around.

Try explaining the goal without mentioning a platform or connector. If that's difficult, the project may still be focused more on the technology than on what people need it to accomplish.

2. Which business problem are we solving first?

Data projects tend to grow quickly. One team wants better reporting, another wants cleaner profiles, and someone else wants personalization, attribution, and several new integrations included in the same launch.

Choose one or two problems that need attention now. That could mean reducing manual reporting, creating a shared account view, or helping marketers update audiences without waiting on IT. Once that priority is clear, it becomes much easier to decide which systems and capabilities are needed right away and which can wait.

3. What would meaningful progress look like?

A completed integration is a milestone. It does not tell you whether the project is helping anyone.

Many organizations struggle to make that distinction. Gartner found that only 22% had defined, tracked, and communicated business impact metrics for most of their data and analytics use cases.

Look for changes in how people work. Marketing and Sales might spend less time comparing reports. Teams may start using the same lifecycle stages. A marketer might create an account segment without submitting a technical request.

These early improvements can be more useful than jumping straight to a large revenue target. They show whether people trust the data and are beginning to use it in daily decisions.

Decide what those signs should look like before launch. Otherwise, the project may be technically complete while the original problems remain.

Understand the Data and Systems Involved

Once the project has a clear purpose, the next step is figuring out what information it actually needs. That does not mean connecting every system the company uses. It means identifying the sources that add useful context, deciding how to handle conflicting information, and being clear about where the data needs to go.

4. Which data sources are truly necessary?

Start with the use case, then work backward.

A shared account view may need CRM records, campaign activity, and website behavior. Another project may also depend on account-based marketing (ABM) data, webinar engagement, or opportunity details. The right mix depends on the decision the team is trying to make.

Separate what is required for the first phase from what would merely be nice to have. Adding more sources creates more integration and data-quality work, so each one should have a clear purpose.

5. What happens when the data does not agree?

Different systems often hold different versions of the same information. A CRM may have one job title, the marketing platform another, and a web analytics tool may not identify the person at all.

Decide which source should take priority before those conflicts begin affecting profiles, segments, and reports. In some cases, the most recently updated value should win. In others, a specific system should remain the authority regardless of recency.

Teams should also be able to see where a field came from. Without that context, it becomes difficult to investigate questionable data or understand why an account qualified for a particular audience.

6. What data needs to move in each direction?

A connector does not always mean two-way data flow.

Some systems bring data into a shared profile but cannot send enriched records, segment updates, or corrected fields back to the original source. Others may allow activation in one destination without coordinating activity across the rest of the technology stack.

Map the required flow before evaluating platforms. Ask what needs to come in, what needs to go back out, and where the final action will happen. That will help uncover gaps between what the project team assumes an integration does and what it can actually deliver.

Plan How Teams Will Use the Data

Bringing information together is only useful if people can use it to make better decisions and take better actions. Before implementation begins, teams should know how they will identify important signals, build audiences, and apply what they learn across campaigns and digital experiences.

7. How will users find the accounts or customers that need attention?

A unified profile can contain plenty of information without making priorities any easier to understand. Users still need a practical way to see which accounts are progressing, which have slowed down, and which may need a different approach.

Consider how the project will organize activity. Will teams be able to review lifecycle stages, recent engagements, time in stage, and important changes from a single place? Can Marketing, Sales, and RevOps look at the same account and reach a similar conclusion?

If users still need to compare several dashboards or export everything into a spreadsheet, the project may have connected the data without making it much easier to use.

8. How will teams build and update audiences?

Think about who will create audiences and what information they will need. A B2B marketing team may want to combine company attributes with actions taken by individual contacts, such as visiting a pricing page, attending a webinar, or returning to product content.

The process also needs to match the campaign's pace. If every new segment requires code, a technical request, or a long refresh cycle, teams may struggle to act while the signal is still relevant. Marketers should know which rules they can manage themselves and when they will still require technical help.

9. Where will the data be activated?

Do not stop at where the information will be stored. Name the places where it will change what a customer or account experiences.

That might include website content, portal journeys, calls to action, recommendations, campaign audiences, or Sales follow-up. The right destinations will depend on the project, but they should be identified before selecting the technology.

Timing matters as well. Some use cases can rely on scheduled updates, while others need to respond to behavior in real time. A visitor returning to a pricing page may call for a faster response than a quarterly account review.

Prepare for Implementation and Adoption

A data project does not end when the integrations go live. Someone still has to maintain the rules, respond when information changes, and help teams make the new process part of their daily work.

The final questions focus on what happens after launch and whether the organization is ready to keep the project moving.

10. Who owns the data, rules, and ongoing decisions?

Ownership can get complicated quickly. IT may manage integrations, Marketing may define audiences, and RevOps may oversee lifecycle stages and handoffs. When those responsibilities are not clear, even small updates can turn into long discussions.

Decide who will manage source priorities, segment logic, access permissions, data-quality reviews, and requests for changes. Executive sponsorship matters, but the project also needs people who own the day-to-day decisions.

Not every task has to be assigned to one team. The important part is knowing who makes the call when a rule needs to change, or two systems disagree.

11. How will teams work from the same view?

Giving Marketing, Sales, and RevOps access to the same data does not guarantee that they will interpret it the same way.

Agree on shared definitions for lifecycle stages, account status, and meaningful engagement. Teams should also know when an account moves from Marketing to Sales, what context follows it, and how disagreements will be resolved.

Without that shared process, the new platform may become one more place for each department to maintain its own version of the account story.

12. How will you measure adoption after launch?

Usage should be part of the success plan from the beginning. Consider what people should do in the first few weeks or months, such as reviewing unified profiles, configuring priority connectors, creating lifecycle stages, or launching the first account segment.

You can also look at whether teams are spending less time assembling reports, submitting fewer routine technical requests, or using the same account definitions in their reviews.

Choose a small set of measures that reflect how the project is meant to be used. A long list of logins and feature counts may look impressive without demonstrating whether the data improves anyone’s work.

If the platform is live but teams continue relying on the same spreadsheets and disconnected reports, adoption has not really happened.

How Ready Is Your Data Project?

Most organizations already understand that data can create business value. Turning that belief into a useful, well-adopted initiative is the harder part. In a KPMG survey, 92% of executives said well-constructed data products were critical to their organization’s success, but only 35% said their initiatives had generated extensive value.

The questions you have just worked through can help close that gap. Take a step back and look at where your project stands.

For each question, choose the answer that best reflects your current level of preparation:

• Yes: We have a documented answer, and the teams involved agree on it.
• Partly: We have discussed it, but some details and decisions remain unresolved.
• No: We have not addressed it yet.

A project with mostly “yes” answers has a clearer direction, but those assumptions should still be tested during implementation. A mix of “yes” and “partly” may indicate gaps in ownership, activation, or data requirements that need attention before the project moves forward.

Several “no” answers do not necessarily mean the project should stop. They may mean the team is evaluating technology before agreeing on what the project needs to accomplish.

Use the results to identify the questions that need further discussion, assign an owner, and decide what must be resolved before selecting a platform or finalizing the implementation plan.

Connect Account Data to Action with Liferay Data Platform

This is where a well-planned data project starts to pay off. Once teams can trust the data and understand what it means, they can spend less time comparing reports and more time improving account experiences.

Liferay Data Platform is the B2B lifecycle intelligence layer built for Liferay DXP. Liferay Data Platform brings CRM, campaign, account, and Liferay DXP behavioral signals into shared profiles and lifecycle stages, giving Marketing and Sales a stronger view of each account and helping them act while interest is still current.

See the complete account story

Unified individual and account profiles bring activity from connected sources into one place. Source-labeled fields indicate where each piece of information came from, while activity timelines show how contacts engage across campaigns and digital touchpoints.

Instead of trying to reconstruct the account story from several reports, teams can quickly see what is happening, which signals matter, and where interest may be building.

Prioritize the accounts that matter

The Account Lifecycle Dashboard organizes accounts across six stages, from Aware to At-Risk. Teams can see which accounts are progressing, which have remained in one stage too long, and where momentum may be slipping.

That shared view gives Marketing, Sales, and RevOps a more useful starting point for deciding where to focus their time and attention.

Act on recent behavior

Marketers can build account-level segments using behavioral activity and attributes from connected sources. When LDP is used with Liferay DXP, those segments can trigger personalized content, calls to action, recommendations, and journey paths as account behavior changes.

The result is a faster path from signal to experience. Teams can respond with content that reflects what an account is doing now, rather than relying on a generic follow-up after the moment has passed.

LDP works alongside the CRM, campaign, and account-based marketing tools teams already use, helping them get more from their existing stack while turning connected data into relevant, account-aware digital experiences.

Start With the Questions That Matter

The right technology can make a major difference, but only when the project begins with a clear understanding of what teams need from the data.

Before choosing a platform or finalizing an implementation plan, make sure the buying committee agrees on the problems it is trying to solve, the information it needs, and how that data will be used once it is connected.

Liferay Data Platform helps B2B teams bring CRM, campaign, account, and Liferay DXP behavioral signals into shared profiles, lifecycle insights, and more relevant digital experiences.