The Top 22 Social Media Monitoring Tools 2026

As generative AI reshapes how people research, learn, and make decisions, a new discipline is emerging: Generative Engine Optimization (GEO). Just as SEO helped brands get discovered on Google, GEO ensures they appear accurately and positively within AI-powered platforms like ChatGPT, Gemini, and Copilot. With millions of consumers now turning to generative engines instead of search engines, GEO is fast becoming essential for marketing and PR professionals looking to influence how their brand shows up in this new discovery layer, where conversations, not clicks, determine visibility.

What is Generative Engine Optimization (GEO)?

Why Should Marketing & Insights Teams Care About GEO?

How Does GEO Work? Key Mechanisms & Signals

What's the Difference Between GEO and SEO?

Increase Your GEO Readiness with Meltwater

Generative Engine Optimization (GEO) is the practice of ensuring that AI platforms such as ChatGPT, Google Gemini, Llama, etc., provide accurate, positive, and up-to-date information about your brand when users ask questions. These platforms are referred to as Generative Engines, Answer Engines, or Large Language Models (LLMs). They are increasingly used by consumers to research purchases and make decisions.

GEO is a way of making sure that AI platforms give people the right information about a company’s brand and products. 

For example, if a person asks ChatGPT: “What is a good family car for camping trips?” then the auto manufacturers would want ChatGPT to suggest their SUV models, and list the benefits. To make sure that happens, the auto brands need to use GEO.

GEO ensures your brand shows up correctly within these AI-generated responses.

The practice of GEO involves several steps, but it is mostly focused on creating, structuring, and publishing content in the best way to influence the responses given by AI Generative Engines. 

In this article we’ll go into the detail of how GEO works, why it’s important, and how you can use it to make sure your brand is featured positively in AI platforms.

Sometimes, generative engine optimization (GEO) is referred to as answer engine optimization (AEO). Learn more about the differences and similarities of GEO and AEO, and take a look at the best AEO tools.

For a long time marketers have been able to rely on the fact that consumers almost exclusively use Google to research buying decisions. So they have been able to use Search Engine Optimization (SEO) to ensure their brand’s website appears in the organic search results, or use paid search advertising to buy ads on relevant search results. 

This is a highly effective way of targeting the right audience at the right time. But now things are changing.

LLMs aren't just another channel. They sit on top of this ecosystem. They synthesize everything into a single conversation.

Allie Konchar, Partner & Chief Client Officer, Omniscient

Changing user behavior: AI + conversational search

Increasingly, consumers are using tools like ChatGPT to research their buying decisions. Data from Meltwater’s 2026 Global Digital Report shows that ChatGPT.com is now the fifth most visited website on the web.

While search engines remain popular, many search queries now produce an AI generated summary that often provide enough information to divert users away from clicking through to websites, because their question has already been answered. McKinsey reports that around half of all Google search queries already produce AI generated summaries, and that number is increasing all the time. 

With conventional web search, consumers are performing research manually, trying to find trustworthy sources and sifting through information to reach the answers they seek. But with Generative Engines, the AI is performing the research automatically, using its existing base knowledge alongside supplemental information pulled from more recent online sources. A search engine shows users where to find answers, while a Generative Engine just gives them the answer. 

For marketers, the key takeaway is that few top-of-funnel consumers are visiting your website, because during the awareness phase their information needs are being met by Generative Engines. This makes it more difficult to move them down into the consideration phase. 

TIP: For more data around growing AI usage and online consumer behavior, download our 2026 Global Digital Report, featuring nearly 700 pages statistics to help inform your GEO strategies next year.

You already know that everybody is talking about AI, and all of your competitors are having the same discussions as you about what it means for their marketing strategy. Those who move decisively to implement GEO, ensuring their brands are represented clearly and positively in Generative Engines, will capture the largest share of those consumers who start their buying journey with an AI query. 

Those who ignore GEO will lose ground, as growing numbers of consumers turn from search engines to Generative Engines, the size of the audiences that can be reached through conventional search marketing will decrease. 

How do generative engines (LLMs) surface content?

It’s important to understand that while Generative Engines are based on similar technology, they all work a little differently. Broadly speaking they all use two different sources of knowledge to provide an answer to a query: 

<table class="table-primary alternate-color">
  <caption>How Generative Engines (LLMs) Surface Content</caption>
  <thead>
    <tr>
      <th>Generative Engine</th>
      <th>Primary Retrieval Method</th>
      <th>Sources Most Often Cited</th>
      <th>Sources Less Likely to Be Cited</th>
      <th>Notes on Behavior</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>ChatGPT</td>
      <td>Bing search + internal training data</td>
      <td>Reuters, AP News, Wikipedia, Encyclopedic sources</td>
      <td>Social media platforms (X/Twitter, Instagram)</td>
      <td>Prefers authoritative, neutral, structured sources with high trust signals.</td>
    </tr>
    <tr>
      <td>Google Gemini</td>
      <td>Google Search + YouTube + Knowledge Graph</td>
      <td>Reddit, YouTube, Google-indexed blogs</td>
      <td>X/Twitter</td>
      <td>Strongly favors user-generated content, community threads, and Google-owned properties.</td>
    </tr>
    <tr>
      <td>Perplexity</td>
      <td>Real-time web crawling + citation-first retrieval</td>
      <td>News publishers, reputable blogs, research papers</td>
      <td>Low-trust UGC</td>
      <td>Most transparent engine — always cites sources and updates in real time.</td>
    </tr>
    <tr>
      <td>Claude</td>
      <td>Internal training data + selected retrieval</td>
      <td>Academic sources, reputable news, long-form articles</td>
      <td>Short-form social media</td>
      <td>Prefers long-form text and well-structured explanatory content.</td>
    </tr>
  </tbody>
</table>

Training Data: All LLMs begin by being trained on a huge volume of existing content and data — we’re talking about dozens of terabytes (a terabyte is 1,000Gb). This training data comes from a wide variety of sources (including your website), and gives the LLM its base knowledge about the world. The LLM does not have any knowledge of anything that happened after its initial training. 

Live Web Search: To overcome the knowledge cut-off problem, the training data is supplemented with fresh information gathered from the internet. If the Generative Engine thinks that a user’s query would benefit from more up to date information than it already has, it fetches new content from trusted online sources and works that into its response. Google uses its own search engine to find fresh information, while ChatGPT uses various sources, including Microsoft Bing.

It’s also important to note that AI does not quote any of this content verbatim in its responses. Much like a human, it uses the information it has learned to inform its own answer, and that can include information from various sources, including the press, competitors, consumer reviews. So don’t expect it to always be on-message!

Another key point is that unlike a search engine, an LLM does not have an index of content which it searches to find answers. It would be impossible to search ChatGPT for all mentions of your brand — that’s simply not how it works. 

An LLM is more similar to a human brain, in that it has a lot of knowledge stored in patterns and relationships between words and concepts. It is extremely difficult, verging on impossible, to examine and understand the detail of an LLM’s learned knowledge because of the sheer scale and complexity; this is a challenge referred to as Black Box AI. 

But we do understand how Generative Engines work at a high level, and we can analyze the kind of responses they produce for relevant queries, which gives us insight into how we should optimize our content for increased visibility.

What content features improve GEO-visibility?

Bear in mind that when you’re optimizing content for Generative Engines, the goal is to write copy that is easier for AI to digest and incorporate into its responses.

Clarity: Avoid overly elaborate language. Do not use corporate-jargon. Keep it simple, professional, and to the point. Leave no room for ambiguity. 

Authority: Wherever possible back up your statements with data from reputable sources, quotes from experts or industry leaders, and reference-able proof points. 

Structure: Organize your pages well with clear titles, headings, and subheadings. Use heading tags (H1, H2, etc) correctly to specify the hierarchy of your content. 

Recency: AI platforms look for more recent information from trusted sources to supplement their base knowledge, so in both owned and earned media, aim to publish fresh content recently.

In many respects GEO shares principles with good SEO practice. If you write consistently high quality content which addresses the needs of your target audience, and structure it correctly on well designed, standards compliant web pages, you will succeed.

First you need to understand your starting point. Meltwater’s GenAI Lens is a tool that gives brands insight into how they are discussed by all major Generative Engines, including ChatGPT, Claude, Gemini, Perplexity, Grok, and Deepseek. 

With GenAI Lens you’ll be able to understand how your brand is already featured in LLMs, what source websites are used in those responses, and whether outdated or inaccurate information is being used. 

We know that LLMs pull content from the web, which they use to inform their responses. So whatever is said about your brand online will significantly affect how Generative Engines talk about your company. 

Start with your own website, this is the first place LLMs will look for information about your organization. But also focus on trusted, high authority third party sites like the mainstream news and specialist media within your industry, because these are the kinds of sources that LLMs will use. GenAI Lens can show you which websites the leading LLMS use to source information about your brand. 

Once you have a comprehensive audit of how your brand is currently portrayed online, you can perform a gap analysis against your desired messaging, and build a plan for how to reach that objective.

Tip: AI brand monitoring, AI media monitoring, and LLM monitoring will help you understand your online footprint. Learn how to track your LLM visibility and how to track LLM brand mentions.

An important difference between GEO and SEO is understanding how people search differently when using Generative Engines. Users interact conversationally with AI, and are likely to ask more complex questions in natural language, compared to simple keywords or short queries in a search engine. So it’s useful to get an idea of what kind of questions people will ask about your brand or industry, to help plan your GEO content.

Tip: Learn more about AI visibility for retail brands.

Unlike search engines, at present the leading Generative Engines do not share data on popular user queries, so it’s not easy to find out exactly what people are asking about your business. But you can look at popular keyword searches associated with your brand, and brainstorm the most likely questions people will ask Generative Engines. 

You can also use a social listening platform, like Meltwater Explore+ to analyze social media conversations around your brand and industry, to gain insight into common questions. Once you have mapped out all of the most likely questions people might ask, you can start creating content that answers those questions.

Tip: Learn how to connect social listening with generative engine optimization. 

Conventional SEO was built around search queries but GEO requires thinking in concepts, context, and authority — you need to focus on the intent of the query, rather than simply trying to match keywords. 

LLMs prioritize sources that provide comprehensive, well-structured, and contextually rich content. Focus your content strategy on:

Educational depth: Long-form resources that answer questions end-to-end. Publish explainers, FAQs, and data-backed insights that answer “how” and “why.”

Credibility signals: Citations, quotes, and data from reputable sources (analyst studies, thought leadership, or trusted media).

Rich media: Generative Engines pull information from videos and images as well as text content, so make use of varied content formats. 

Consistency across channels: LLMs learn from media, social, and owned content together; ensure your narratives are aligned across them.

The key thing is to ensure that your content is genuinely helpful in answering those questions you mapped out. If your content is too focused on sales messages, it’s less likely to be used by the LLMs.

TIP: Discover innovative AI-generated content examples to enhance your digital strategy.

You can optimize the content published on your website and owned channels, but LLMs also source information from trusted third party websites. That means PR has a key role to play in ensuring your brand is featured in high authority earned media, including news features, expert comment from your spokespeople, product reviews, and any other kind of brand story traditionally generated through a media relations campaign.

Tip: Learn more about the importance of earned media for GEO and about PR Pitch GEO optimization.

The tricky part is that unlike advertising, which can tell exciting and attention grabbing stories, PR professionals are limited to working only with the facts. But while you cannot always control the outcome of media outreach activity, ensuring that PR and GEO are aligned will help increase the volume of third party sources that feature the right messaging.

Tip: Learn how GEO is reshaping PR strategies.

Meltwater’s GenAI Lens gives you the ability to track your GEO performance over time, so you can understand whether your strategy is working well and spot areas where you need to improve. The tool provides visualizations that show brand sentiment, emotion, key phrases, people, products and things mentioned, alongside citations.

Armed with this information you can identify gaps in your GEO strategy where you might need to create more or better content. You can also discover which third party sources have the greatest impact on your GEO performance, and use that information to optimize PR outreach to focus on the most important media. 

Like SEO, this is a process of constant iteration and improvement. GEO should not be seen as a one-off project that will generate positive results in perpetuity, but rather an ongoing activity that needs to be integrated with the broader marketing mix.

Tip: Learn How to Measure PR Performance Across LLMs and Generative Search, and understand how to report on LLM visibility.

Which Media Sources to Prioritize for GEO

When an LLM processes a user query, it can often detect that the response might require more recent information than it has access to in its original training data. In that situation it will look online for more up to date content that will help it to form a more accurate answer, but where exactly do Generative Engines look for this information?

At Meltwater we used GenAI Lens to research which content sources the leading AI platforms were most likely to reference in their responses, and there were distinct differences between them all:

Open AI ChatGPT: Heavily favors text-based news and newswires (Reuters, AP, PR Newswire) and reference sites (Wikipedia). Much less likely to cite social media and UGC. 

Google Gemini: Leans towards high quality UGC from sites like Reddit and YouTube, as well as other online sources within the Google ecosystem. Does not index X/Twitter content. 

Google Search AI Overviews: Highly focused on UGC from Reddit and YouTube, as well as Facebook, Yahoo and LinkedIn. 

xAI Grok: Strongly skewed towards conversational UGC from X and Reddit. Less likely to cite traditional reference sources like Wikipedia, YouTube or academic sites. 

Unlike SEO, where most practitioners were happy to optimize only for Google, in GEO we have to consider the nuances of several different platforms; at the very least ChatGPT and Google AI Overviews. In short, it’s good practice to ensure you have up to date content propagated across a wide range of platforms where LLMs might look for supplemental information.  

In terms of which online sources are most likely to be referenced overall, we looked at several categories and charted the most frequently cited websites:

<ul class="medium">
	<li><b>Social Media & UGC</b></li>
    <ul>
		<li>reddit.com: 43.1%</li>
		<li>youtube.com: 17.9%</li>
        <li>facebook.com: 11.1%</li>
		<li>linkedin.com: 9.2%</li>
        <li>quora.com: 5.6%</li>
	</ul>
	<li><b>Consumer Reviews</b></li>
	<ul>
		<li>glassdoor.com: 21.6%</li>
		<li>indeed.com: 20.6%</li>
        <li>trustpilot.com: 15.7%</li>
		<li>bbb.org: 9.9%</li>
        <li>yelp.com: 8.0%</li>
	</ul>
	<li><b>Travel</b></li>
    <ul>
		<li>tripadvisor.com: 83.2%</li>
		<li>expedia.com: 10.0%</li>
        <li>booking.com: 6.8%</li>
	</ul>
	<li><b>News & Media</b></li>	
    <ul>
		<li>yahoo.com: 26.5%</li>
		<li>prnewswire.com: 10.8%</li>
        <li>reuters.com: 9.0%</li>
		<li>forbes.com: 6.7%</li>
        <li>usnews.com: 6.7%</li>
	</ul>
    <li><b>Academic & Science</b></li>	
    <ul>
		<li>nih.gov: 53.6%</li>
		<li>researchgate.net: 14.5%</li>
        <li>sciencedirect.com: 10.0%</li>
		<li>jhu.edu: 7.5%</li>
        <li>cdc.gov: 5.8%</li>
	</ul>
    <li><b>Market Research & Consulting</b></li>	
    <ul>
		<li>statista.com: 18.8%</li>
		<li>mordorintelligence.com: 16.3%</li>
        <li>gartner.com: 14.9%</li>
		<li>mckinsey.com: 13.5%</li>
        <li>cbinsights.com: 13.0%</li>
	</ul>
    <li><b>Business & Financial</b></li>	
    <ul>
		<li>investing.com: 14.1%</li>
		<li>morningstar.com: 13.2%</li>
        <li>nasdaq.com: 11.4%</li>
		<li>nerdwallet.com: 10.4%</li>
        <li>seekingalpha.com: 8.8%</li>
	</ul>
    <li><b>Government & Public Sector</b></li>	
    <ul>
		<li>weforum.org: 20.6%</li>
		<li>europa.eu: 17.8%</li>
        <li>canada.ca: 12.7%</li>
		<li>imf.org: 11.5%</li>
        <li>sec.gov: 10.1%</li>
	</ul>
</ul>

Many teams focus on keywords, backlinks, and meta tags, but LLMs prioritize context, authority, and relevance. GEO requires content that answers full questions with clear, verifiable information, not keyword stuffing or link chasing.

2. Ignoring source credibility and transparency

AI models reward trustworthy, well-cited content. Publishing unverified claims, outdated statistics, or missing citations can lower visibility or lead to inaccurate AI summaries of your brand. Always include reputable data sources, authorship, and dates.

3. Failing to monitor how your brand appears in LLMs

Without ongoing media monitoring, brands miss when GenAI models misrepresent their products or replicate misinformation. LLM tracking tools like Meltwater’s GenAI Lens can surface these blind spots and help correct or update narratives quickly.

What is Generative Engine Optimization (GEO)? & How to Do It

Giving customers what they want is what turns a lead into a buyer, a buyer into repeat business, and repeat business into referrals. Knowing how to create this perfect match between “need” and “knowledge of need” requires businesses to have the right tools and data to guide the way. This is what we call customer intelligence platforms help provide.

Customer intelligence, also known as consumer intelligence, comes from a variety of sources. Customer intelligence analytics analyze specific details, including what customers have bought, what they’re searching for, and what they’re engaging with. It helps companies better understand their customers’ needs and the journeys they take to fulfill them.

Once you have customer intelligence, you can go about transforming all that data into actionable consumer insights.

Let’s look at how a dedicated customer intelligence software can help you connect the dots and inform your next best actions.

What is a Customer Intelligence Platform?

Why Do You Need Customer Intelligence Software?

Top 8 Customer Intelligence Platforms 2026

Use Cases for Customer Intelligence Platforms

Leveraging Meltwater for Your Customer Intelligence Strategy

FAQs about Customer Intelligence Platforms

What Is a Customer Intelligence Platform?

Customer intelligence platforms (CIPs) are powerful software tools that gather, analyze, and utilize customer data. They help companies gain a deep understanding of customer behaviors and preferences, which will help them make better business decisions.

These tools consolidate multiple data sources into a single place for easier comparison and trendspotting. 

You might also hear CIPs called customer intelligence software or customer intelligence tools.

Customer intelligence tools provide valuable insights into various customer segments. You can learn more about their engagement levels, likelihood to buy from you in the future, and potential churn rates, for example.

Applied to business decisions and growth potential, customer intelligence software offers a myriad of benefits:

Holistic insights: All your data in one place helps you better spot trends and patterns, which can lead to better customer experiences.

Stronger customer loyalty: Understanding customers’ needs and wants on a deeper level gives you an easy in — a way to connect with them better than anyone else.

Increased competitive advantage: Knowing your customers better than the competition does helps companies differentiate their offerings from lookalikes, making it easier to cut through the noise.

Greater business agility: With a constant finger on the customer’s pulse, businesses can pivot swiftly and respond to changes without reinventing the wheel or slowing operations.

CIPs have the potential to revolutionize the way in which businesses engage with their customers. They enable personalized experiences at scale, such as hyper-targeted recommendations or customized offers based on customers’ preferences. This level of personalization not only increases customer satisfaction but also drives long-term loyalty and brand advocacy.

Customer intelligence platforms help you pull data together to see trends and patterns and turn intelligence into insights. Here are eight customer intelligence software solutions to fuel your strategy.

Meltwater consumer intelligence combines AI, market research, and data science to create one of the most insightful customer intelligence platforms on the market.

Designed with global enterprises in mind, brands can discover what their customers think and feel based on billions of data points. 

Meltwater surfaces trends and patterns companies might not have thought to look for. This leads to new opportunities to learn more about your customers and meet them wherever they are, even in places you have yet to explore.

Best for: segmenting audiences based on attitudes, behaviors, and other criteria. 

All data is delivered in real time and updated on a continuous basis, meaning you’re never out of touch with what’s happening with your customers.

Fill out the form below to get a free tour of our platform.

Online searches can reveal a lot about your customers, which is what makes Semrush such a valuable customer intelligence software. This platform helps businesses gain a competitive edge in the digital landscape with insights into web presence for themselves and their competitors.

One of Semrush’s standout features is the ability to perform in-depth competitor analysis. Users can track competitors’ online strategies, including traffic sources, keywords, and top products. This gives businesses direct insight into missed opportunities, allowing them to refine their own strategies.

Semrush also provides a treasure trove of data on customer behavior and preferences. Through keyword research tools, businesses can identify high-value keywords and phrases to help them rank higher in search. 

Best for: ensuring businesses are resonating with their target audiences and can better connect and engage with their audiences authentically. 

When exploring customer intelligence solutions, it’s essential not to neglect free options like Google Analytics. Google Analytics grants you access to essential search-related data that’s relevant, accurate, and always up to date.

Detailed insight into website performance

One of its shining features is its ability to provide detailed information about website traffic and user behavior. It tracks metrics such as page views, bounce rates, session duration, and conversion rates, shedding light on how users engage with your website. Using customer segmentation, businesses can dissect their audiences by demographics, devices, locations, and even interests.

Best for: integrating with other tools like Google Search Console and Google Ads. This gives marketers a comprehensive view of their efforts meaning businesses can correlate their marketing activities with website performance.

Tip: Google Analytics also provides some important PR KPIs and marketing metrics like content marketing metrics, and social media KPIs.

ActionIQ pushes customer data directly into your CRM to empower your sales team to have informed conversations. Data based on customer behaviors and activities evolves into detailed customer profiles and audience segments, which can lead to more personalized experiences.

Best for: identifying at-risk customers, upsell opportunities, and brand advocates who can help you sell more, grow your brand awareness, and measure brand awareness. 

ActionIQ also integrates with other popular tools, including Salesforce, Shopify, and Facebook Ads. 

When you want to know more about your customers (or lookalike audiences), it helps to go straight to the source. That’s precisely the idea behind YouGov, a customer intelligence tool that connects you directly to millions of would-be customers.

This self-service tool gives you actionable answers from your audience, from in-depth research to one-off polls and surveys.

Best for: getting straight to the source to learn more about trends, wants, needs, buying behaviors, motivations, and more. With over a million profiling points, you can create deep customer personas that unlock more value for your marketing campaigns.

Customer intelligence platforms allow sales reps to spend time on accounts and leads that are most likely to close. Leadspace develops buyer profiles and personas that can make these leads easier to identify.

Predictive B2B profiles based on intent and personas

It uses a combination of first-party and third-party data from leading B2B companies. 

Tour the Meltwater Media Intelligence Platform

Top 8 Customer Intelligence Platforms & Software 2026

Effective marketing is about being obsessively customer-centric. You need to have your customers’ pain points and desires at the center of everything you do. And you need to do it in a remarkable way.

Wes Mathew, Head of Marketing, UKI and India, Meltwater

The online customer journey describes a consumer's path throughout all product, brand, and company touchpoints that help decision-making. Consumers usually look at a product or brand several times before deciding to take action. They can also flow both forward and backward through the various stages in response to different stimuli and sources of information.

To set your digital customer journey up for a win, you need a clear understanding of all components involved. These include your target group, customer behavior, optimal communication channels and content formats to use, and most importantly, the user intent at each stage of the journey.

Let’s dive into the customer journey framework and how to optimize the process by creating a customer journey map and using metrics that matter when analyzing the customer journey.

What Does an Online Customer Journey Look Like?

Who Does the Customer Journey Map Follow?

Analyzing the Customer Journey by Personas

Optimizing Customer Journey Mapping by Stage

What are the Benefits of Creating a Customer Experience Map?

What are Customer Journey Mistakes to Avoid?

How Do I Know if I’ve Been Successful at Optimizing the Online Customer Journey?

How to Use a Customer Journey Map Template

A customer journey is the accumulation of every step a customer has taken before and after purchasing from your company, and the various emotions they felt each step of the way. These steps are often signified by touchpoints, or moments where the customer interacts with your brand in some way.

Customer journeys are relevant for any company, regardless of the product or service they sell. 

Two examples of what a customer journey could look like include:

B2C Customer Journey: You’ve moved cities and need new weather-appropriate clothes. You’re scrolling through Instagram and see an ad that you click on. You decide not to buy anything, but you sign up for that company’s email list. After you receive an email coupon, you go to the site to finally buy the item that initially caught your eye. 

B2B Customer Journey: You need to get new software for your PR team. You Google the options, see the top results, and click through to a G2 Crowd report. You find reviews on some of the options and then go straight to their respective websites to schedule demos. Due to budget constraints, you wait a few months and then eventually purchase your top choice.

These may sound relatively straightforward in writing, but tracking this process is often not so simple. 

Sales and marketing teams are not the only departments in your company that should be actively using your customer journey to drive business activities.

Customer journey maps are a necessary communications tool for a variety of reasons. They help you:

Target your efforts: PR and comms pros need to understand how to reach their company’s target audiences effectively. Budgets are often tight, and every activity needs to deliver a proven ROI. If comms professionals keep pitching publications that their ideal customers are not actually reading, then you’re just wasting resources, or vanity pitching top-tier publications to feed the ego of your client

Uncover content ideas: Responsible communication activations should keep customer needs and pain points in mind. By keeping your comms team versed in the customer journey, you can more easily identify the best storylines to pursue

Enable cross-functional collaboration: Any customer-facing or customer-targeting department in your company (so, arguably, everyone) can benefit from some version of a customer journey map. More specifically for comms, your marketing and sales teams are likely creating resources to help move customers along their journey and down the marketing funnel. Comms teams need to know about these resources to ensure they’re not duplicating efforts, take the lead in using them to secure more backlinks to the company’s website, alongside company interviews in those earlier-determined key publications

Mira is Meltwater’s AI-powered teammate. It helps teams track brand impact, identify trends, and respond to media shifts in real time, providing clearer insight into how communications contribute across the customer journey. Take a self-guided tour to see how Mira can support your team.

When defining what the online customer journey looks like, brands should try to consider all possibilities. There are tons of paths that lead to the same destination, and not every path is linear.

Let’s say you want to purchase a new pair of headphones. You might start thinking about how and when you plan to use your headphones. For example, do you want to be able to connect to a mobile device? If so, does your mobile device support a wired connection, or will you need Bluetooth headphones?

From there, you might do a simple Google search to get a feel for the available styles, brands, colors, and price points. Then you might narrow down your options, watch some product videos, and then look at some product reviews from other users before making a purchase. Some people even look for coupon codes or discounts before deciding where to buy.

See how many different actions a consumer might take before choosing their headphones? This approach applies to just about any product your customers buy online. They might take these actions in this order; they might not. There might be other steps they take.

As a brand, your job is to learn more about consumer behavior and the steps your customers take when making buying decisions. This is where customer journey mapping tools like the Meltwater Suite can add value to your strategy.

Before we discuss tips for optimizing the online customer journey, let’s first briefly discuss the steps involved. In general, there are five main stages to explain the customer journey:

During the first step of the customer journey (awareness), the user becomes mindful of a need or want. Sometimes, they come to this realization on their own (e.g., their headphones break). Sometimes, the brand presents a problem the user didn’t know they had.

At this stage of the journey, the person is actively looking for options. The second step is defined by the user’s intent to gather all the relevant information to make good decisions. The user has all the basic information about a subject already from step one. The consideration/evaluation stage is about narrowing down options and comparing.

During this stage, the user is ready to make a decision. At the transaction stage of the customer journey, it’s important to keep things as simple as possible, so as not to overwhelm the customer and thereby prevent the sale from going through.

It’s at this stage of the B2B online customer journey that the ‘second moment of truth' takes place. The second moment of truth refers to the customer’s experience with the company they’re considering after they’ve become aware. This can occur both before purchasing the product, such as experiencing a hands-on demonstration on TV, but it may also happen after a purchase. This is usually the case in the modern age of online and live shopping when a customer doesn’t truly experience the product until after it arrives.

A second moment of truth that occurs before purchase will have a greater influence on whether a customer will pay for a service or product. On the other hand, a second moment of truth that happens after purchase will have a bigger impact on their satisfaction and continuing relationship with a brand, therefore affecting reputation.

During this stage of the cycle, two-way conversation is key. Customers and prospective leads need to be kept "warm." Even if the lead didn’t respond to further call to actions, there’s still an opportunity to re-engage with them.

What happens after the transaction? The customer's journey should be seen as a loop – just because the transaction is complete doesn’t mean it’s game over. For instance, there might be further needs that come with the purchase, like repair services or upgrades.

Tip: Learn more about how to build and maintain customer loyalty and watch our free on-demand webinar to learn how to map and visualize your customer journey.

Every map is designed to help users find their way to a specific place. In the business world, a customer journey map fulfills this same purpose. But instead of guiding customers, it serves as a blueprint for brands to better understand and optimize the customer buying experience.

A customer journey map can be defined as a visual representation of how customers discover and buy products. It plots all the possible actions a customer might take to reach a decision.

Items that make up a customer journey include:

All other touchpoints between customers and brands

Putting all of these things onto a single map makes it easier for business owners and brands to see connections between them. By understanding the paths your customers take and the relationships between touchpoints and actions, brands can improve these paths to create optimal outcomes.

Customer journey maps work for all types of customer touchpoints, whether you’re a business-to-business or a business-to-consumer brand.

However, there’s a difference in user journey mapping when you’re serving clients vs consumers vs customers.

A person who anticipates professional support and/or consulting from a business, often the case with professional service providers like attorneys, tax professionals, and financial institutions.

The terms ‘customer’ and ‘client’ are often used interchangeably, but the difference between customer and client matters in the buying journey. Using the word ‘client’ implies a long-term relationship between the buyer and the business. Clients typically receive ongoing advice or product and service recommendations from a business. This isn’t true for customers, who typically deal in transactions only. The relationship may end when they complete the purchase.

A person who buys goods and services from a business, either for personal or professional use.

Customer classification matters because priorities can affect customer values. For example, an end-user who is buying something for a business might have to consider more than their personal preferences. The buying journey is usually longer, involves more decision-makers, and the decision may affect the business as a whole.

Also, what the customer is buying can indicate how much information and how many touchpoints they need to make a decision. For example, choosing an oven for a home is a much costlier investment than choosing a new shelf. Customers will need plenty of information from the manufacturer to select their oven, will likely compare many options and brands, and read lots of reviews.

Tip: Read about the most common types of customers and learn how to approach them.

A person who purchases goods and services for personal use, usually in a repetitive cycle where items are continually consumed and replenished.

The consumer buying process looks and functions differently from the customer journey because items are usually low-cost and not intended to last forever. Examples of consumer purchases include toothpaste, food, household items, and clothing. The stakes for making a “right” decision are low and don’t often require a lot of research and comparison shopping before choosing to buy.

Client vs Consumer vs Customer in the User Journey Mapping Process

Knowing the difference between customer vs consumer matters when getting inside the customer journey. Knowing the type of customer you’re selling to can help you better understand their needs and priorities. Brands can anticipate shorter or longer buying journeys, provide enough helpful resources, and conduct more effective, proactive outreach to send buyers to the next stage.

Buyers begin their journeys in different places. Adding to the previous example, a buyer who has never had a set of headphones may have more research to do than a person who is trying to replace their favorite headphones that recently broke. Someone who found a set of headphones they love might already have brand loyalty, which can lead to a faster user journey. 

So, as there are different types of customers, there are also different types of customer journey maps. 

Let’s look at four customer journey map examples:

<table class="table-primary">
<thead>
<tr>
<th>Type</th>
<th>What it is</th>
<th>What it includes</th>
<th>How it helps</th>
<th>When to use it</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>Current-state customer journey map</strong></td>
<td>A view of how customers experience your brand today</td>
<td>Touchpoints, actions, emotions, and pain points across the journey</td>
<td>Identifies gaps, friction, and areas for improvement</td>
<td>Assessing existing experiences or planning improvements</td>
</tr>
<tr>
<td><strong>Day-in-the-life customer journey map</strong></td>
<td>A broader look at a customer’s daily activities and context</td>
<td>Customer routines, behaviors, needs, and challenges beyond your brand</td>
<td>Provides deeper insight into customer motivations and priorities</td>
<td>Exploring unmet needs or new opportunities</td>
</tr>
<tr>
<td><strong>Future-state customer journey map</strong></td>
<td>A vision of the experience you want customers to have</td>
<td>Ideal interactions, desired outcomes, and improved touchpoints</td>
<td>Aligns teams around a shared goal for the customer experience</td>
<td>Planning changes, launches, or long-term strategy</td>
</tr>
<tr>
<td><strong>Persona-based customer journey map</strong></td>
<td>A journey mapped for a specific audience segment</td>
<td>Persona goals, behaviors, touchpoints, and expectations</td>
<td>Supports more relevant messaging and targeted experiences</td>
<td>Different audiences follow different paths</td>
</tr>
</tbody>
</table>

Brands need to get into the mindset of their customers to know how to create the right experiences for them. Knowing what your customers need and want helps you decide which products to sell and how and when to communicate. A customer journey map organizes this process so you can optimize the customer journey at every touchpoint.

See also: Mapping Unpredictable Customer Journeys

The Importance of Customer Journey Mapping for Brands

Customer experience (CX) plays an important role in turning customers into returning customers. Studies show that customers not only expect a great experience, but 86% are also willing to pay more for it. What’s more, 72% of customers will tell others about their excellent experience, which can lead to more opportunities to wow more people!

That said, user experience isn’t something you should leave to chance. Brands need to take an active role in shaping how customers experience your business, whether it’s via your website or call center or even in person.

The right customer experience software can help. It gives you insights into how customers are already experiencing your business so you can find opportunities to improve.

We’ve done some of the hard work for you by rounding up the eight best customer experience tools to include in your CX strategy. Let’s dive in!

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