This article first appeared here: https://marketing.toolbox.com/articles/what-is-marketing-intelligence-definition-best-practices-use-cases-and-tools
What is Marketing Intelligence?
Marketing intelligence is defined as any actionable and data-oriented information that can be used to build an effective marketing strategy. This means data about your customers, your efforts, and your competitors that will help you make informed decisions around the pillars of marketing: product, price, promotion, and placement. Marketing Intelligence is a subset of Business Intelligence. Business Intelligence is all of the data you collect in order to make strategic decisions and monitor the health or your company, across many disciplines like finance, HR, operations, etc. Marketing Intelligence is specific to your marketing efforts.
Business intelligence helps you to understand the WHY of your marketing. Why do I care about the metrics that I’m looking at? Why am I running this campaign? It’s the topline goals that you’re working against, the core business outcomes. Business intelligence includes many strategies, tactics, and data that aren’t unique to marketing, such as customer retention, sales volume, cost of hiring, etc. – data that can influence marketing, but not be part of marketing operations.
Marketing Intelligence, the WHAT, is a combination of your internal information, and the information that you can gather about what’s going on with your customers, your competitors, the general cultural landscape. It’s the action that you take to meet your goals and the data that helps you understand if your efforts are working.
Artificial Intelligence refers to the HOW – it’s the technology you can use to synthesize that information and analyze it, whether it’s in a spreadsheet or using some sort of a machine learning assisted model. One of the greatest challenges of marketing intelligence is the sheer amount of marketing data we must contend with. Artificial intelligence helps us process this data and arrive at actionable insights much faster.
Learn more: What is Audience Management?
Why is marketing intelligence important and who needs it?
Marketing Intelligence is important if you want to make data-driven decisions to power strategic marketing. A shockingly small number of companies use data to make decisions, so it’s an opportunity to find a competitive edge if you are. The most recent CMO Survey found that only 37.7% of CMOs use data to make decisions.
Why is this an opportunity for you? If only 37.7% of CMOs are using their marketing intelligence – then 62.3% are not using anything and are guessing at what they should be doing.
The primary use case for marketing intelligence is to run more intelligent campaigns that are set up for success based on data-driven decisioning. For instance:
- You have a better sense of what your customers want to see, and when.
- You know the seasonality of your sales cycles and can ramp your campaigns up and down accordingly.
- You know that when you release a new version of your product that people contacting support will spike.
- You can prepare your staff and documentation in anticipation of those spikes.
- You know which subject lines get higher open rates from your email campaigns and you can adjust based on your analysis.
Think about your content marketing plan and how you can use marketing intelligence. Creating new content can be a time-intensive and expensive process. Wouldn’t it be more effective to have data that told you what to create and when? Using resources such as Google Trends and SEO data to understand search trends can help you put together a plan that you can measure. You can then use your social data to understand the best time of day to post content so that you have the best shot of your audience seeing your content. By knowing the search trends, you’ll also know which content you should be putting money behind, and with which keywords.
The above example is a very straightforward use of marketing intelligence. You can see how using data to make decisions can enhance the effectiveness of your marketing efforts so that you’re working smarter, not harder.
Learn more: What is Customer Data Management (CDM)?
Marketing Intelligence best practices and tools
There is no one single tool that can do everything you need for proper marketing intelligence. It takes a combination of tools to put together a comprehensive marketing intelligence plan and analysis, and in this section, we suggest some practical tools to execute the core steps in the marketing intelligence process.
Marketers who leverage marketing intelligence successfully tend to have four core steps in the process. These are:
You need to collect the right data that aligns with your business goals – this is why having business intelligence first is super helpful. The best way to map out your data is an exercise called KPI (key performance indicator) mapping. In a nutshell, you’re figuring out how your data points map back to your business goals, ensuring that you’re looking at the right data, not all the data. Business goals are usually around revenue, so if you’re not sure or can’t get the information right away – start there.
Next are the KPIs that feed up into your goals. Let’s say you have a business goal of 100k in revenue for the year and generate your revenue through sales on your website. If you can work backward and figure out what 1 sale is worth, you can then figure in your conversion rates along the sales process and that will become your KPI map.
Let’s assume a completed cart, with everything purchased, is worth $1,000. How many will you need to meet your goal? 100 completed carts. Suppose customers abandon their carts 90% of the time before finishing their purchase. How many carts would you need? 1,000. That’s a great KPI because if that number falls short, you definitely miss your goal.
Let’s walk further up the marketing funnel. How many visitors to the site do you need? To achieve 1,000 cart fills, suppose that the same general 90% attrition rate holds, which means that 90% of the people who visit your site don’t fill a cart? You’d need 10,000 site visits to achieve 1,000 filled carts, to achieve 100 completed carts.
This is your KPI map; at each stage, you know what number leads to the next stage, and you will assign each KPI to someone to own and manage.
Once you’ve completed your KPI map, you can start setting up your various software systems to collect data. Tools to consider for data collection are Google Analytics or Omniture and Social Listening tools like Talkwalker, AgoraPulse, Sprout Social.
Once you’ve collected the right data, you need to analyze it to understand what’s going in. The analysis takes many forms, but one of the most simple, yet powerful, forms is basic regression analysis. Do any two or more metrics have a mathematical relationship to each other? For example, many marketers find themselves with a surplus of data, especially towards the top of the funnel, from impressions to engagements to activities. Do any of these metrics have a correlative relationship with the KPIs we outlined in KPI mapping? If there’s a strong association, we can move onto proving causality, but if there’s no relationship at all, we can rule out a metric’s importance.
You can do basic regression analysis with nothing more than a spreadsheet and some common formulae but it becomes cumbersome as datasets get larger and more complex. This is where the use of artificial intelligence – specifically, machine learning – comes into play. Machine learning tools can do massive regression analysis of every possible combination of variables and produce mathematically sound outputs in a very short amount of time.
Other techniques that marketers seeking marketing intelligence will need include classification, clustering, and dimension reduction. All these functions serve to make marketing analytics data more clear and easier to understand.
Once you’ve analyzed your data, putting together visuals to help your team understand the metrics is the next step. This may come in the form of a dashboard or a report. Unless you can see what the data says on a regular basis, you cannot make decisions with it.
Most companies opt for manual reports – think daily emails or static power points. A better option includes some automation. Automation within your reporting takes away a lot of the human error that comes with copying and pasting numbers (we all screw this up) and frees up your time to work through interpreting the data and determining what to do about it.
If you’re looking to start with simple automation, Google Data Studio is a great visualization tool. Google Data Studio integrates natively with many third-party tools and offers connectors for those that it doesn’t. You can pull Google Analytics data right into Data Studio and it will update in near real-time, allowing you to see what’s happening across all your marketing efforts.
Now that you can see your data it’s time to do something. If you’ve collected the right data, you’ll be able to see what actions you should be taking. That said, the first three steps in the process are only worthwhile if you make the commitment to follow through with the recommendations.
One of the best practices we’ve established with ourselves and our clients is to create high-level scenarios. What do these scenarios look like? They cover the different analysis situations that your data will take on a regular cadence. What do you do if the number you’re looking at goes high? What do you do if the number you’re looking at goes low? What do you do if the number you’re looking at doesn’t change? By covering at least those three scenarios you won’t have to spend too much time figuring out what actions to take – you can go ahead and take them.
Learn more: What is Marketing Automation?
If you want to reap the benefits of marketing intelligence – faster decisions, better decisions, reduced risk, innovative marketing – then it’s incumbent on you to get started today. Start your journey by following the CAVE framework outlined above. Pick a test case, a target, a proof of concept that follows the steps we outlined, and see how using marketing intelligence strategies, tactics, and tools will lead you towards the data-driven decision-making your company demands of you. Embrace it wholeheartedly, and you’ll leave your competitors in the dust.
Need help with your marketing AI and analytics?
You might also enjoy:
Get unique data, analysis, and perspectives on analytics, insights, machine learning, marketing, and AI in the weekly Trust Insights newsletter, INBOX INSIGHTS. Subscribe now for free; new issues every Wednesday!
Want to learn more about data, analytics, and insights? Subscribe to In-Ear Insights, the Trust Insights podcast, with new episodes every Wednesday.