As a business owner, you likely have to make dozens of decisions every day, from strategic decisions like how to position your product in a new market to minor ones like how to write a social media post. With decision overload, how can you ensure you’re choosing the best possible option for your business?
The first step in making good decisions is having the right information. And when it comes to getting good information, one of the best things you can do for yourself is set up marketing intelligence systems. Here’s what marketing intelligence is and a few ways you can collect and analyze it.
What is marketing intelligence?
Marketing intelligence is information related to an organization’s marketing efforts, including how your messaging resonates with your target market. It’s a subset of business intelligence, the broader system of data collection that allows companies to analyze business performance. You can collect market intelligence wherever your customers are. Focus groups or surveys are examples of actively gathered marketing intelligence. Data from your systems from things such as advertising campaigns, automated post-purchase surveys, and social media monitoring tools are examples of passively gathered marketing intelligence.
Marketing intelligence can come from your own suite of marketing tools, such as your Instagram analytics page (which shows you the number of likes and followers on your profile) and website (which has information on visits and purchases). It can also come from third-party data, such as industry research reports or outputs from social media sentiment analysis tools that show you how people talk about your brand online.
Types of data to collect
There are two types of marketing intelligence data: quantitative and qualitative. They work together to help form a complete picture of a company’s marketing presence.
- Quantitative data. This data can be counted and expressed in numbers—it’s objective, not opinion. Examples of quantitative data include customer ratings, website traffic, and net promoter scores (NPS). Marketers should ensure the data is a reliable reflection of their target market by checking that survey respondents’ demographics align with overall customer demographics).
- Qualitative data. This is any data that can’t be expressed in numbers. Customer comments, focus group recordings, user screen recordings, interview logs, and any other expression of information that isn’t numbered are examples of qualitative data. Although it may be harder to make conclusions from qualitative data due to its unstructured nature, qualitative data can provide valuable insights. For example, a comment on an ad such as “I don’t get what this is for” provides insight about what a potential customer thinks that would be hard to infer from quantitative data alone.
What decisions can marketing intelligence help you make?
Marketing intelligence provides information about your target market, so it can help you make any decision related to that audience. This includes decisions about your marketing efforts, such as where to run advertising campaigns, and decisions about your product, including what price it should be. Some other decisions that marketing teams can make with marketing intelligence are:
- What target customer to market to
- What product(s) to develop
- What marketing channels to leverage (for example, social media or search advertising)
- How to communicate points of differentiation from competitors
- What new market opportunities are most attractive to expand into
5 ways to collect marketing intelligence
- Focus groups
- Competitor research
- Social sentiment tracking
- First-party digital audience data
Here are five common ways to collect marketing intelligence:
1. Focus groups
A focus group is a group of people—either potential or current customers—that a business gathers to provide feedback on their marketing. You may choose to ask them about any number of elements of marketing—be it pricing, brand positioning, product features, or perceived product benefits of your product or service. Ask your focus group open-ended questions, a format that allows for unexpected information. The main benefit of this format is the level of depth that the answers can provide.
Similar to focus groups, surveys include a series of questions to people in the target audience. Surveys involve a series of responses to pre-set questions. Ecommerce brands often send post-purchase customer surveys to their customers to better understand why they purchased and whether they’re satisfied with their purchase. The answers to these questions can provide additional context on the company’s marketing mix and messaging. Relative to focus groups, this method is cheaper and there is the possibility to draw quantitative data from a large sampling of answers.
3. Competitor research
Competitor research is the practice of analyzing your competitors for insight that can inform your own decision-making. It can include a review of competitors’ products, pricing, promotions, distribution channels, or customer experience. It can be focused on direct competitor intelligence, analyzing companies with similar products and target market, or indirect competitor intelligence, analyzing companies with a similar target market but different, alternative product.
Competitive analysis can take many forms but is typically delivered as a report compiled by a researcher or analyst. Marketers can use this type of business intelligence to discover their own competitive advantage as well as to identify gaps in the market, spot industry trends, and understand where their own products may be falling short in relation to other companies.
4. Social sentiment tracking
Social sentiment tracking involves monitoring and analyzing digital channels including social media platforms, online forums, and review sites to gauge public sentiment about a brand, product, or industry. This kind of research could show you that your customers repeatedly complain about your product’s price point, or that they appreciate your fast shipping times. Often, marketers will aggregate various sources of public sentiment through a tool like Hootsuite or Idiomatic to identify high-level market trends.
5. First-party digital audience data
Digital audience data refers to the collection and analysis of data related to online consumer behavior, interactions, and customer preferences. It includes brand data such as annual sales records, website analytics, and social media analytics. Marketers can use this data to gain insights into their audiences’ demographics, interests, and browsing behavior. One of the advantages of this data is that businesses can collect it from their existing marketing channels—instead of needing to set up a focus group or ask people to fill out a survey, businesses can simply review their existing Google Analytics or Facebook Page data.
How to analyze marketing intelligence data
- Prepare the data
- Conduct exploratory analysis
- Conduct statistical/hypothesis analysis
- Compile insights
- Prepare next steps
1. Prepare the data
Whether it’s qualitative or quantitative data, you’ll want to make sure it’s as clean as possible before you analyze it. One step to take is to remove irrelevant data points. For example, if you’re trying to figure out how many potential customers visit your website, make sure you exclude site visits from your own employees. You’ll also want to review the data for any egregious outliers since a single data point can skew the whole dataset so that it no longer reflects reality. For example, if you want to figure out the average order value of your online store, you might want to remove the $1,000 worth of merchandise a single person bought if all the other orders are around $50. That’s because if you don’t remove it, one large order would substantially raise the data’s average order value without representing the majority of customers.
2. Conduct exploratory analysis
When reviewing marketing research, marketers often have a specific question they want to answer, such as “Will customers be mad if we raise our prices?” or “Are most of our customers parents?” But before jumping into deep analysis, it’s helpful to look for any trends in the data that stand out.
Exploratory data analysis is the practice of reviewing a dataset for significant patterns or correlations, outside of a specific hypothesis. It helps to ask if there are diversions from the norm or unexpected comments that jump out. This type of analysis, typically aided by visualizing the data in charts or graphs, can help identify opportunities for follow-on analysis that are easy to miss if you’re too focused on looking for the answer to just one specific question.
3. Conduct statistical/hypothesis analysis
The goal at this stage is to understand what the data can and can’t tell you. Analyze quantitative data by reviewing for statistical significance. Analyze qualitative data by categorizing the data into themes or highlighting the most insightful data points (for example, a focus group manager might highlight a note from a participant that they had never heard before).
Be aware of technical limitations of the data gathered from digital tools, and look for gaps where you may be missing data. For example, Apple’s iOS 14 update limits the data shared from iPhones, so some website analytics will report very few visitors from iPhones. This doesn’t mean there is a dearth of people visiting your website from smartphones—it might just mean that data on the actual amount of visitors is not captured.
4. Compile insights
This is the process of turning the findings from your analyses into a summary that another stakeholder could understand. This can be a written report, charts, or executive summary. The goal of sharing insights is so that the insights can help inform business decisions. For example, an insight that your target audience is moving off of Facebook and onto Instagram could impact how your marketing team allocates your social media advertising budget. These reports should be easily understandable by other stakeholders, including the leadership team.
5. Prepare next steps
Sometimes, the marketing intelligence leads to a clear decision, such as whether or not to launch a new type of marketing campaign or product. In these cases, this stage is about planning next steps related to the decision. Other times, the process uncovers that more information is needed. For example, the data might show that many of your customers use TikTok when considering a purchase, but may not give enough information about what kind of TikTok accounts they look to. So the next steps may include planning how to get that follow-up information.
Market intelligence vs. market research
Market research is a subset of market intelligence. Both disciplines attempt to gain insight into your market, but market research data is obtained through activities you take with the primary goal of understanding the market or customer, such as focus groups or surveys.
Marketing intelligence, on the other hand, refers to information gleaned through a broader array of activities including active and passive research, or information gathered in the course of running marketing campaigns, such as social media engagement, website activity, or sales records.
Marketing intelligence FAQ
Is marketing intelligence only relevant to large businesses?
Marketing intelligence is relevant for businesses of all sizes. With the rise of affordable tools to interact with customers directly—such as Hootsuite and SurveyMonkey—as well as free social media platforms, businesses of any size are able to easily access marketing intelligence.
Does marketing intelligence involve only external data sources?
No, marketing intelligence doesn’t just include third-party external data like social media sentiment information. It also includes first-party, internal data, like how users are behaving on your website.
Is marketing intelligence a one-time process?
No, gathering marketing intelligence is an ongoing process. It employs a mix of active and passive processes, such as sending out surveys (active) and reviewing website analytics (passive).