The Consumer Intelligence Maturity Model

Its benefits are significant: when used correctly it can feed into better marketing campaigns, inform product development, and ultimately improve sales, customer satisfaction, and loyalty.

This guide will help you understand how you can maximize your consumer intelligence strategy to gain access to these benefits. Plus, we’ll provide some actionable steps to improve based on your current consumer intelligence maturity level. 

What’s in this guide? 

• The benefits of consumer intelligence
• What is this Consumer Intelligence Maturity Model?
• How to use this guide and glossary of terms
• The four stages of consumer intelligence maturity
• Stage 1: Beginner
• Stage 2: Mid-level
• Stage 3: Advanced
• Stage 4: Embedded
• Creating a strategy to level up your consumer intelligence maturity
• Actionable steps to boost your consumer intelligence maturity
• Your next steps

The benefits of consumer intelligence

So, why should you care about generating consumer insights? Here are just some of the benefits of improved consumer intelligence.

• Boost your ROI: According to Forrester, investing in a customer-first operation will yield an ROI increase of at least 700% over 12 years.
• Gain a competitive advantage: Anticipate trends and stay on top of consumer preferences, meaning you can move quicker and smarter than your competitors.
• Supercharge your marketing: Create messaging that speaks to your customers by getting to know their wants and needs better.
• Improve customer satisfaction: By listening to consumers, you’ll be able to make key improvements to the customer experience that’ll keep people coming back for more. 

Gaining a better comprehension of your industry and competitors, as well as prospects and existing customers, will mean your business can make data-driven decisions that impact your bottom line.

Let's see how Brandwatch’s Consumer Intelligence Management Maturity Model can bring these benefits to life. 

What is this Consumer Intelligence Maturity Model?

We’ve developed a framework which is designed to help your brand assess your current level of consumer intelligence maturity. This guide will provide you with a roadmap for how to optimize your consumer intelligence strategy moving forward. 

We leveraged internal expertise and frameworks which help companies who thrive with consumer intelligence to continue to innovate. We've also observed how standard use cases based on data monitoring can develop into a strategy that incorporates consumer intelligence into almost every major business decision.

You’ll soon be able to understand where you sit on the model, and then discover ways to progress on your consumer intelligence journey.

How to use this guide

This guide serves as a tool for you to evaluate your organization’s current consumer intelligence maturity level. It’ll help you identify and address operational, strategic, and governance challenges within your organization.

But first, let’s get familiar with some common terminology.

Glossary of terms used in this guide

Here are some definitions of words and phrases we use throughout this guide.

• Data source: A data source refers to any platform or system which provides information about consumer behavior, preferences, demographics, or interactions. A data source could be anything from a social media platform like Reddit, to an internal CRM system which manages customer data.
• Monitoring: Monitoring data sources describes continued observation of data which might show trends or events in real-time. It’s a more passive method compared to analysis.
• Analysis: Analysis of data sources refers to examining, processing, and interpreting data to discover helpful and actionable insights.
• Social listening: Social listening can be used as a method of collecting consumer intelligence. It refers to the process of monitoring and analyzing online platforms and social channels for mentions and trends relating to your brand, product, or industry.

Now, let’s look at the maturity model and discover how you can use it effectively.

The four stages of consumer intelligence maturity

Let’s dive into our Consumer Intelligence Maturity Model. Here’s a quick overview.

For each stage, there are expected behaviors or use cases that can help you understand where your organization fits on the model. It’s worth noting that there is no necessary connection between the size of an organization and its consumer intelligence maturity.

In fact, slower moving corporations might find there’s plenty of work to be done to mature their consumer insights program and better understand their consumers.

Here are the different stages of the model.

Stage 1: Beginner

Companies in the earliest stage of consumer intelligence maturity are characterized by the following behaviors:

• Beginner-stage organizations are likely to monitor one or two data sources in a basic way. They might collect overall metrics to provide regular reporting over time and focus on detecting major patterns or shifts. For example, measuring website traffic, customer satisfaction scores, or online share of voice
• They’ll likely have a single non-analyst collecting data, and a limited number of internal recipients for the reports or insights generated
• Data informs a small number of use cases and impact on company decisions is minimal 

Stage 2: Mid-level

The second stage of consumer intelligence maturity can be recognized in the following behaviors: 

• Best practice analysis of various data sources, including continuous market analysis and segmentation 
• Skilled analysts examine consumer intelligence data with confidence. Yet, a feedback loop is missing for analysts to understand how their data is used across the company 
• Data is continuously informing team activity as a result of reporting and live insights. Insights inform business decisions across some organizational functions, for example some ad hoc analysis is done for internal departments and stakeholders

Stage 3: Advanced

Organizations in the third stage of consumer intelligence maturity tend to operate in the following ways:

• Data blending and triangulation helps inform deeper insights. Analysts will partake in everything from historical trend analysis to forecasting and predictive analytics
• Dedicated analysts continuously examine consumer intelligence data. Data and insights are accessible beyond the analyst team. Some feedback is provided back to analysts on the usage of their insights
• Insights inform business decisions across a range of organizational functions

Stage 4: Embedded

Organizations that are operating at the highest level of consumer intelligence maturity will exhibit the following behaviors:

• Data blending and triangulation is continuously experimented with and expanded. API integrations are used to deepen analysis
• Cross-functional insights sharing is the norm. Analysts benefit from an effective feedback loop that drives better analysis and insights delivery
• Consumer intelligence informs almost every major company decision and dictates company investments. There are significant human and financial investments in this area and a recognition of the competitive advantage it provides

Creating a strategy to level up your consumer intelligence maturity

Finding where your organization fits within the maturity model is usually straightforward. The hard part comes when trying to formulate a strategy that helps you move towards the next level.

Your approach to maturing can be made easier by: 

• Starting small but with purpose: For example, if you’re still just setting up tracking, make sure you’re collecting the metadata you’ll need to be able to segment and analyze in meaningful ways later. Or if you’re already collecting data, you could prioritize integrating it into a unified platform to help create actionable, shareable insights.
• Setting goals and key performance indicators (KPIs): These should be based on what you want to gain from advancing your consumer intelligence. This will help you decide which areas you need to focus on.
• Investing in trustworthy tools: The world of data can be confusing. You’ll need tools you can rely on in terms of customer support, specialized services, compliance, scalability, and flexibility.
• Not worrying about perfection: A successful data strategy is likely to be refined over the years, so don’t focus all your efforts on your data collection. Make time to develop how you can start telling compelling stories with your data. This is what drives action – tangible, memorable insights that the whole company can refer to and work with.

It’s also important to remember that an organization can move both up and down the scale of maturity. Complacency or slow-moving progress could mean that an organization that is relatively mature today could fall to a less mature stage as time goes on.

Brandwatch’s most successful clients are those with an organization-wide understanding of the value of consumer insights. So, investing time into the company outlook on consumer insights can prove to be one of the most beneficial ways to level up your maturity.

Let’s look at some specific areas you can focus on when it comes to improving your consumer intelligence.

Actionable steps to boost your consumer intelligence maturity

Let’s look at some specific areas within consumer intelligence to discover where you can level up your maturity.

• Your data
• Your team
• Your impact

Your data

Investing more time into consumer insights can often be enough to advance to the next stage – especially for companies at the Beginner level. Of course, doing this effectively starts with having clear business goals. Get key stakeholders involved in this process, and once you have these goals defined the purpose of your data analysis will be much clearer. 

Getting to know the platforms you use for consumer insights generation is also essential. Make sure that platforms are set up to help you address key business questions and goals. Following proper onboarding and enablement processes with these platforms and putting time into your set up can help with this. Remember, generic onboarding doesn’t work for everyone, so consider making use of any professional services or learning opportunities your vendor has available.

Focusing on sharing your insights appropriately is also key. Remove barriers between your findings and the rest of your company and invest time into making these insights accessible to all appropriate areas of the business. Afterall, consumer insights can have a short shelf life – timeliness of delivery is important.

After understanding your platforms properly and putting efficient systems in place to share your insights, you can take your consumer intelligence to the next level by implementing integrations and maximizing data augmentation. This is something which is largely done by those at the Advanced and Embedded stages and is a key example of investing further in your consumer insights journey. 

Brands who make use of API integrations within their chosen consumer insights platforms can expand their datasets and understand their audience even further. Uploading your own first party customer data and analyzing it alongside online data unlocks new insights for many analyst teams. The idea is to build a holistic view of the voice of your customers and connect consumer insights to hard ROI metrics. 

How to level up at each stage

At the Beginner stage of maturity, it's all about getting set up. That can mean establishing objectives, creating benchmarks, and understanding what different data sources can offer. At this stage, it's important to experiment and make decisions that can scale with your developing consumer intelligence program. Those at the Beginner stage of maturity likely won’t use integrations or data augmentation. Addressing these issues can help businesses enter the next stage of maturity. 

Similarly, Mid-level businesses are more likely to focus on quantitative data – for example gathering website views or conversions to make general conclusions. These companies can level up their maturity by learning how to incorporate qualitative data into their analyses, and questioning how their first-party data might complement consumer insights from other data sources. 

Advanced and Embedded businesses will incorporate both qualitative and quantitative data into their analyses. They’ll use engaging storytelling in their reporting and presentations and to create digestible narratives without compromising on the complexity of the data. Working on minimizing speed to insight will help these companies level up, so data can be shared in near-real time. Advanced businesses can also benefit from implementing API integrations to get deeper insights. Data blending should be the norm and data analysts should compare data sources to gather a complete picture of their consumers. 

Embedded businesses will likely leverage large datasets in combination with artificial intelligence for efficiency and to discover new perspectives. They’ll combine multiple data sources, such as social listening and sales data, to tell effective stories with the data. They will constantly ask questions on the data, push the boundaries, and understand any limitations. 

Additionally, Embedded businesses will utilize data augmentation to plug gaps in existing data. For example, they might create customer profiles based on existing demographic data which helps to improve customer segmentation. Or perhaps they benefit from behavior simulations, which generate hypothetical consumer behaviors to build robust customer journey models for deep analysis. Some businesses at this stage might even build a custom consumer insights hub that’s tailored to their specific needs, pulling data from various internal and external sources into one unified space.

Your team

A capable consumer insights team isn’t defined by how many data analysts you employ – it’s based on their skill level and synergy. No matter where you currently sit with your consumer intelligence maturity, if you can upskill the people that handle your data and ensure they work in efficient ways, you’ll likely see increased benefits company-wide. 

Having capable data analysts also includes their ability to tell stories with insights. They should always make sure they’re sharing data in a way that’s audience appropriate and easy to digest. 

No matter where you are in your consumer intelligence journey, you’ll likely benefit from upskilling your team and streamlining your processes. 

How to level up at each stage 

Companies at the Beginner stage of maturity tend to have less investment in their data team, and there might be issues with siloing among data analysts – perhaps with several single data handlers sitting in different areas of the business. For example, social listening access may be limited to the social media team within marketing. Addressing siloes as well as upskilling or better resourcing data managers – who might have lower skill levels and limited time – can help your business level up. 

Companies at the Mid-level of maturity will have a bit more focus on gathering and distributing insights, even if team members handling data don’t have an analytical background. They’ll also spend time in consumer insights platforms more productively than those in Beginner stage. Speed to insight will be quicker, and upskilling data handlers into dedicated, skilled analysts will help the business to progress in their maturity. 

Businesses at an Advanced level of maturity might have implemented a triage process for data requests so that areas across the business can request relevant insights for their decision making. The data insights team might even report to a dedicated Chief Insights Officer, or similar, who sits in senior management. This is a significant step up in terms of team and resourcing compared to previous stages. 

Businesses at the Embedded stage will benefit from having highly skilled, dedicated data storytellers who work together efficiently to deliver insights quickly. Team structure at this level can vary drastically and this is to be expected – every business will have different goals. 

Your impact 

Data is only useful if it has an impact. Businesses looking at maturing their consumer insights program should hope to understand how their data is being presented, shared, and understood by the company. 

Even more important are feedback loops: does your insights team hear about how their work is used? What are the outcomes of the data they’ve gathered? Do they evolve alongside your business' goals? 

We touched on this in the data section, but data sharing can be the making or breaking of successful consumer intelligence teams. The way insights are presented and stories are crafted for different audiences is so important. 

This goes hand-in-hand with leadership buy-in, which is crucial for a successful consumer insights team. Without senior management understanding how these insights can benefit their business, it will be difficult to prove the power of further investment, whether that be in terms of head count or new tools. 

Internal success stories are an excellent way to showcase how your data analysts can help internal business units succeed with the help from consumer insights. 

How to level up at each stage 

Businesses at the Beginner stage likely won’t have a culture that appreciates the benefits of consumer data analysis. In some cases, lack of experience from siloed data handlers might mean they don’t understand the power of the data themselves. To advance to the next stage of maturity, data champions must strive to share the value and try to create some visible wins. 

Mid-level businesses will have more focus on how their analyst team is expressing insights. They will step up from simple reporting, for example looking deeper into the actual conversations being had about their brand. However, they might be overloaded with basic requests, which prevents them from developing their reporting practices and actioning feedback. Plus, they might not completely understand how insights are being used, so they can’t improve the impact of their output over time and get that vital leadership buy-in. 

Consumer insights professionals at Advanced businesses will create regular executive summaries to distill data into short, easy-to-digest bullet points for multiple stakeholders to understand. There will be notable executive buy-in, which is crucial when it comes to investing in effective consumer insights data sources and analysis software. Advanced businesses will have confidence that people across the business are reading their reports, and they’ll adjust their processes on a regular basis based on feedback from across teams. 

Analyst teams at businesses in the Embedded stage will pay attention to data presentation, ensuring as many people are possible are leveraging their insights. These businesses will have a deep-rooted culture of data sharing. Many areas of the business will continuously utilize the insights gathered by the team and questions and feedback will be exchanged regularly. At this stage, businesses might benefit from sharing internal success stories on how data has impacted business decisions – demonstrating the value of utilizing insights and sparking more requests. This will further perpetuate internal confidence in the benefits of consumer intelligence, and innovation in the field can continue.