What is marketing analysis?
As a business conducts their marketing operations, they’ll generate a lot of marketing data. This data has the potential to be very useful, but it needs to be collected and analyzed first. Many marketing tools have analytics features which can help businesses to make sense of their data, but these tools are often limited.
In most cases, the data that a tool connects is trapped within that tool. The data from a business’s marketing automation software is only accessible in that software, the data from a CRM platform can’t get out of that platform, and so on. While these tools can often perform analysis on their own data, they can’t communicate with each other to provide a holistic view of a company’s entire marketing situation.
A company can collect all the marketing data it wants to, but all that data won’t do them any good unless they can view it all at once, analyze it all in one tool, and get it out to their marketing team in an easy-to-digest way.
Business intelligence tools are the perfect solution for managing all of a business’s marketing data. A BI tool can connect to all of the software that a business uses to do their marketing operations, collect all the data from those tools, and analyze all the data together. This process breaks down the barriers between data; after using a BI tool, a marketing team could see data from their CRM, ERP, and automation software all on one chart.
These tools allow marketing teams to use data in completely novel ways. Now that data isn’t siloed within individual tools, team members can spot trends and find relationships between data sets that would have been invisible beforehand. Marketing teams can also communicate with other departments, using non-marketing data with their own to find new insights.
Of course, marketing data isn’t useful unless the marketing team can actually use it. Marketing employees often do have some sort of training in business or data analysis, but they may not have the technical expertise to make use of an extremely complex analytical tool. In fact, many older systems require their users to have programming and statistical knowledge to properly operate them.
With modern, self-service BI solutions, any employee can analyze and visualize the marketing data they need to do their job properly. These tools are designed from the ground up to be user-friendly and intuitive, unlike software solutions of the past. Marketing teams can take control of their own data, and use it themselves to make decisions and drive insight.
Business intelligence tools represent a paradigm shift in marketing analytics. With a full-stack, no-code, self-service marketing analysis solution, businesses can leverage their marketing data in novel and useful ways. To stay competitive, businesses need to let data drive every part of their operations, and marketing analytics is a key component of that.
What features does a BI tool need for marketing?
Most of the features businesses will want in a marketing analytics tool are general-purpose features that can be used to analyze any type of data. These features help ensure a good data experience for every member of the team, and make it possible for even data novices to pick out actionable marketing insight.
Most businesses deploy their marketing through many different channels. For example, a business may run the same ad on TV, before YouTube videos, and on social media sites. With a marketing analysis tool, that business can compare the analytics from all those different channels and figure out which one is the most effective.
Businesses don’t always use the same strategies on the same marketing channels. The marketing strategy for a print ad won’t be the same as the strategy for a social media campaign. Since these strategies are so different, it can be hard to directly compare how effective they are.
BI tools can help to compare different marketing channels in ways that don’t distort. They help marketing teams get a clearer image of what channels are effective, which aren’t, and–with the right data and insights–might be able to help figure out why a channel isn’t effective.
Dashboards and visualizations
A major advantage of business intelligence software is access to useful and visually-interesting data visualizations. Many non-BI tools present their data in text-based reports, which can be difficult for the average person to understand. Even someone who knows how to properly interpret a report won't be able to interpret it very quickly.
BI tools can take data sets and streams and automatically build data visualizations out of them. Data visualizations are graphics like charts, maps, graphs, or tables, which present potentially complex data analysis in a visual way. They’re essential for helping the average marketing employee understand data.
Users can interpret data visualizations much faster than text-based reports, which only need minimal training to understand. People may not understand how to read a report, but they can instinctively understand what a line going up on a chart means. Some visualizations may need more explanation, but in most cases, they’re pretty simple. With data visualizations, users can understand their data in a much more visceral, instinctive way.
Marketing teams can combine their data visualizations all onto one page, or a few pages. These pages, called dashboards, allow users to view key metrics and track business health all from one place, instead of having to click around to see different visualizations individually.
Dashboards streamline the data analysis process. They help users see related metrics at a glance, compare them quickly, and draw simple, intuitive insights from them. Users can track important metrics and gauge their data in real time.
In user-friendly, self-service BI tools, teams and individual users can build and edit their own dashboards and visualizations. Users can build new dashboards ad-hoc, without any involvement from IT or a BI expert. When an employee wants to build a new dashboard for a project or to see data from a new angle, they can easily make or edit a dashboard to see data in the most helpful way.
Individual users can even adapt their team’s dashboards to their own needs. Users can change how a BI tool displays a certain data stream to them, letting them utilize the visualizations that are the most effective for them.
Much of the difficulty of using a BI tool isn’t that users can’t find the answers they want, it’s that they’re not asking the right questions. Some data trends can be hard to spot, and often, they’re hidden in ways that would be impossible for a human to find. Data mining helps uncover trends and patterns that a human eye might miss by applying novel, machine-led analyses.
Data mining helps find connections between sets of data that might appear completely unrelated. It works backward compared to traditional data scientists, finding relationships without making a guess as to how or why there’s a relationship.
For instance, a marketing team might mine their data on lead generation. Though there’s no reason to suspect a relationship between the two, they may find that leads are less likely to convert in the afternoon. The marketing can then shift all their lead generation calls to the morning, which the data mining suggests might boost conversion rates.
Data mining is a unique advantage that only business intelligence tools offer. Most standalone marketing tools rely on their users to find trends, while BI tools can help users find new relationships beyond superficial ones.
Business intelligence tools can use the past and current data that a marketing team has generated to make educated guesses about what the future will look like. The techniques the tool uses to make these guesses are called predictive analytics.
Predictive analytics are an extremely useful tool for any marketing team looking to plan for the future. Using the forecasts and scenarios offered by the feature, marketing teams can model how different marketing strategies will pan out, calculate how likely a given lead is to convert, and make plans for future opportunities.
For example, predictive models might suggest that demand for a product will surge in six months. The marketing team for this business can then make plans for the future. They might decide to make a major marketing push when demand surges. This would give them a major advantage over businesses that didn’t run that model and make the necessary preparations.
Predictive analytics can also help marketers predict the results of their actions. If there’s a relationship between two variables, it’s simple to predict how one will change as the other is manipulated. For example, a marketing team could model how decreasing ad spend would affect lead generation.
Advantages of marketing analytics
Marketing analytics makes spend more efficient. Marketing teams can easily figure out which of their channels are most effective, find novel strategies to produce leads that are likely to convert, and predict how exactly spend will translate into leads and revenue.
When spend is more efficient, the whole marketing operation is more efficient. Teams can direct spend to where it’s the most useful, and stop spending on projects and channels that don’t produce results. Management will be happy that they don’t have to increase their marketing budget to get more results.
Marketing analytics allows for better decision-making. Instead of making decisions based on vague clues or gut instinct, employees can use data to make wise, informed choices. Thanks to tools like predictive modeling, users can have a fairly good idea of what the results of their decision will be before they even implement it.
Marketing analytics lets teams see the results of their campaigns in real time. With the improved data tracking capabilities of a tool like Domo or Tableau, users can track the data associated with their campaigns in real time (or as close to real time as possible). This helps marketing teams see how their campaigns are performing right from the start.
Tools like dashboards and visualizations accelerate data insights. With the right dashboards, teams can track their campaigns faster and much more effectively than they could with legacy analytics tools. Visualizations help teams analyze their data faster, and boost data literacy.
Cloud-based self-service BI tools help marketing teams interact with data in a more personal way. If a tool is user-friendly and intuitive, then the average user will be more likely to interact with it effectively. Marketing teams usually aren’t very data-savvy, so tools that are as easy to use as possible are the best choice.
Marketing analytics: improving customer outreach with data
Businesses need to make full use of all the marketing tools at their disposal to stay competitive in increasingly saturated markets. With data on their site, marketing teams can use it to make better decisions and drive insight.
Any business can profit from improved marketing analytics capabilities. To find out what tool is the best for your situation, reach out today for a no-cost consultation from our team of experts.