Understanding Marketing Analytics in 2026

Marketing analytics is the practice of collecting marketing data, analysing that data across sources, and finding valuable insights you can use to optimise current and future campaigns.

Marketing analytics software can surface insights that can help businesses maximise their resources and budgets, better connect with their customers, and ultimately grow their revenue.

In 2026, these performance insights are more important than ever as customer expectations rise, and acquiring new customers becomes harder. According to our latest State of Marketing report , we found that 85% of marketers say expectations are increasing, while 69% say customer acquisition is becoming more difficult.

So, how can you build a strong marketing analytics practice at your business? Read on to learn more about what good marketing analytics can do for you and your business, how to overcome common challenges, and how to get started building a data-first mindset in your marketing team.

• AI is making marketing more predictive and more personalised
• Marketing analytics helps businesses turn customer data into strategic decisions
• Connected, first-party data is important for understanding your customers

To better understand why there is such a low rate of satisfaction with marketing data, let’s take a look at some of the biggest challenges teams face.

Your average marketer will have data from their website, email, socials, paid ads, and much more. While there is no shortage of marketing data to process, the challenge is being able to decipher what matters.

Due to this, data often sits across different tools and formats, and can make it difficult to compare performance, identify trends, and connect your work to revenue.

As privacy expectations rise, we are losing access to some traditional tracking methods. Cookie changes and tighter privacy regulations mean businesses can no longer rely as heavily on third-party data.

This is pushing marketing teams to focus more on first-party data and building stronger direct relationships with audiences.

Customers now move between websites, social media, email, streaming platforms, search engines, and in-store experiences before making a purchase.

Tracking these journeys accurately is difficult when data is siloed across multiple systems. This makes it harder to personalise campaigns and measure ROI effectively.

Many businesses still store marketing, sales, and customer service data separately. This creates disconnected reporting and an inconsistent customer experience. Imagine the frustration customers feel if they need to explain their business again to the service teams after already going through it with sales.

On top of this, it’s hard to thrive as a marketer when you don’t have all the information at your fingertips.

Collecting data is only part one of marketing analytics. Teams also need the time and tools to interpret the data and use it to make decisions.

Particularly in fast-moving marketing environments, reporting often becomes reactive rather than strategic. For example, teams frequently pull data only when they have a reporting meeting or notice something is going wrong.

We are finding that the businesses seeing the strongest results are the ones using connected analytics tools and AI to automate reporting and make quicker decisions across campaigns.

Thirty-three per cent of marketers strongly agree they gain insights fast enough for impactful decision-making. Using AI in marketing can speed up these insights and help you make decisions faster. Here’s how.

• Predictive segmentation: AI helps marketers group customers based on predicted behaviour and intent, not just past actions.
• Campaign forecasting: Teams can use AI to predict campaign performance and identify which strategies are most likely to drive results.
• Real-time next-best actions: AI can recommend personalised offers, content, or actions based on live customer behaviour.
• AI-powered optimisation: Marketers can use the data from AI to optimise content across different channels in real time.
• Agentic analytics: Agentic AI not only shows you the data, but it can also recommend or trigger actions automatically within your approved guardrails.
• AI search measurement: As AI-powered search grows, marketers are finding they need to adapt their strategies to measure visibility across AIO and GEO.

Businesses already using AI in marketing are seeing measurable gains, including a 20% increase in marketing ROI , a 20% increase in customer satisfaction, a 19% increase in conversion rates, and a 19% decrease in marketing costs.

Now, let’s take a look at a few of the benefits you can achieve if you have a good system for measuring and using marketing analytics.

Analytics takes the guesswork out of your marketing. Instead of assuming your customers are engaging with your messaging, marketing analytics provides proof of digital engagement.

Marketing analytics gives you a unified view of your customers by helping you understand their digital interactions, preferences, and responses to your marketing. This process involves in-depth digital marketing analysis.

Seeing this unified customer profile helps you understand the customer journey. You can then create more personalised experiences that will drive conversions and business growth.

Marketing analytics show you how your campaigns are performing as they happen. You can refine strategies using data through techniques like A/B testing. You can then use the data to pivot towards new strategies.

Real-time data collection is far better than evaluating data once a campaign is complete. Access to real-time analytics and data reporting helps you step in and optimise before it’s too late.

Marketing rests on analytics. If you don’t have the numbers, it’s impossible to ask for further investment or justify the work you’re doing.

How you show this can vary, but ultimately it needs to tie back to commercial outcomes. So in marketing, conversions should be your top concern, but other metrics like engagement and CTR can all be part of the path to conversion.

Modern marketing analytics are no longer about reporting on past performance. Today, businesses are increasingly using predictive and prescriptive analytics to anticipate customer needs and make faster decisions.

This shift toward predictive and agentic analytics is becoming increasingly important in 2026, as businesses move from simply analysing customer history to anticipating future behaviour and intent.

Marketing analytics pulls data from across your customer journey to help teams understand performance, customer behaviour, revenue impact, and campaign effectiveness.

While the exact metrics vary between industries, there are a few core marketing metrics that most teams regularly track to guide decision-making.

CAC measures how much it costs to acquire a new customer. You can find this by dividing total marketing spend by the number of customers acquired.

CLV estimates how much revenue a customer is likely to generate over their time with your business. It’s commonly calculated by multiplying the average purchase value by the customer lifespan.

Conversion rate measures the percentage of users who complete a desired action, such as making a purchase or filling out a form. You can calculate it by dividing total conversions by total visitors or users.

ROI refers to how much revenue your marketing activities brought in compared to what you spent. It’s calculated by subtracting marketing costs from revenue generated.

CTR measures how many people clicked on a link or advertisement after seeing it. You can find this by dividing total clicks by total impressions.

CPC tracks how much you pay each time someone clicks on an ad. You can find it by dividing ad spend by total clicks.

This measures how actively audiences interact with your content through actions like comments, shares, saves, or likes. You’ll be able to see this on each channel.

This measures how many people leave your website without clicking on another page. This will be tracked by channel.

This measures how many people opened your email campaign. You can calculate it by dividing opened emails by delivered emails.

This tracks how many times your content or ad was shown to people. Most platforms calculate this automatically.

A clear strategy for using your marketing data can move you beyond surface-level reporting and help you make better decisions. The goal here is to connect marketing activity to commercial outcomes and identify where your budget will have the biggest impact.

Here are the simple steps for getting started.

Start by identifying what you want to improve. Often, this is increasing revenue, but sometimes the focus is more on building brand awareness or improving lead quality.

For example, if your goal is to improve lead quality, you might want to identify which customers have the best return compared to what they cost to acquire. In other words, look for the customers who generate more revenue for the business than it took to bring them in.

Defining clear goals makes it easier to focus on the right data.

Once you know your goals, choose metrics that directly support them. Avoid focusing only on vanity metrics like impressions or follower counts if they don’t lead to revenue.

For example:

• If your goal is profitability, track CAC and ROI.
• If your goal is retention, track churn and customer lifetime value.

Modern marketing data is often spread across multiple systems, including CRMs, websites, paid advertising platforms, ecommerce tools, email software, customer service systems, and more.

Connecting these data sources creates a clearer picture of the customer journey and helps teams make faster, more accurate decisions.

You can do this by moving to an all-in-one platform like the Agentforce 360 Platform.

Dashboards are a great way to keep on top of your metrics day to day without having to dig. It will save you a lot of time down the road if you focus on building a dashboard that clearly displays trends, performance changes, customer behaviour, and opportunities for improvement.

This allows both the marketing team and leadership teams to quickly understand what’s working well and what needs attention.

Marketing analytics becomes valuable when insights lead to action. Use your findings to test new campaigns, improve customer journeys, adjust budgets, personalise experiences, or support sales follow-up.

As AI-powered analytics continues to grow, many businesses are also using automation and predictive insights to make these decisions faster and at greater scale.

To learn more, watch our demo of Agentforce Marketing .

In order for marketing analytics to be effective, it needs to become part of the culture at your company. Your people, processes, and technology will all need to shift to be more data-oriented.

Here are a few ways to make marketing analytics a priority on your team.

Before you can implement a fantastic marketing analytics strategy, you need to establish who’s in charge of the data. Determine the key stakeholders and collaborators who will need access to the marketing data. Establishing who’s in charge will save you time later when it comes to tracking down different data points.

In addition to establishing stakeholders, it’s important to make sure that marketing and sales teams are aligned on goals. When these two teams share business objectives, it’s easier for them to work in tandem to knock these goals out of the park.

Start making data a central part of more team discussions and make it a habit to start and end projects with data.

In today’s marketing departments, there are so many tools used to connect with customers. Each of these tools is gathering its own data, and that can make pulling a holistic marketing report a nightmare.

Instead of trying to pull data from all of these sources, try an integrated marketing analytics platform that acts as a single source of truth. You’ll want to choose a platform that’s designed for marketers so that it’s easy to use and understand.

With centralised, integrated data sources, marketers can get more accurate metrics and stay informed on key performance indicators.

With the demise of third-party cookies, first-party data will become even more important. First-party data comes from your digital marketing channels, including user behaviour on your website.

Examples of first-party data include:

• Customer support chat transcripts
• Social media interactions
• User behaviour on your website

In order to take a first-party data approach, you’ll need to put in place new ways to gather customer information. Lead generation campaigns are valuable for gathering consumer data in exchange for quality content. Survey questions are a good way to understand what customers are looking for and segment them into different groups for marketing. Asking for customer feedback through reviews aids in building expansive consumer profiles.

First-party data will also help you create personalised content for specific customers, which is important because customers who see content tailored to their interests are five times more likely to engage with a brand.

There are numerous tools for marketing analytics that all make it easier to foster a data-driven marketing culture. Marketing analytics software will assist your team in sifting through data to determine relevant insights.

Look for a marketing analytics platform that acts as an all-in-one tool. A quality marketing analytics platform will bring in data from disparate places so you can view it all together.

Flight Centre Travel Group, one of the world’s largest travel retailers, wanted to better connect its customer data and personalise marketing across its brands.

To do this, they brought in Data 360 and Agentforce Marketing to bring together their customer data across websites, apps, email, and loyalty touchpoints. This allowed the team to build data-driven audience segments, offer personalised deals in real time, and keep a better track of customers across channels.

As a result, they saw the following improvements:

• 44% higher average booking value for loyalty members
• 43% increase in website deal interactions
• 27% more sales from personalised emails
• 60% increase in new subscribers
• 65% reduction in martech spend

In 2026, businesses are using connected data and AI-powered insights to predict customer behaviour, personalise experiences in real time, and make faster marketing decisions with more confidence.

As customer journeys become more fragmented and expectations continue to rise, having a clear view of your marketing performance is becoming a non-negotiable for growth. Businesses that can connect their data and act on their insights quickly will be in a far stronger position to generate revenue in the current competitive environment.

To learn more about how Salesforce can help you unify your marketing data and automate campaign optimisation, explore Agentforce Marketing Analytics.