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What is call analytics and what does it do for marketers?

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What is call analytics and what does it do for marketers?

Call analytics software manages the inbound phone channel (including both landlines and mobile phones), handling tasks from assigning call tracking numbers to measuring, monitoring, analyzing and reporting the resulting caller data and campaign results. These platforms provide call tracking, recording, routing and attribution tools to enable these functions.

Even before the coronavirus pandemic disrupted American lives and businesses, the telephone – particularly the smartphone – had become an integral part of the consumer purchase journey. When faced with the worst public health crisis in more than a century, U.S. consumers used the telephone more than ever before.

Newer technology may get the headlines about record data usage, but the old-fashioned telephone call spiked during and after lockdowns. As the pandemic first took hold, Verizon network data showed phone calls increased by 20% as people were connecting more over the phone than in person. That percentage has remained steady with phone calls now coming in at almost 19% above pre-pandemic times. Today the duration of those calls also
remains significantly higher, with people talking almost 29% longer.

For the vast majority of customers (both consumers and business buyers), talking on the phone to a person who can answer their questions is one of their preferred ways of interacting with businesses. Phone calls provide businesses with an opportunity to offer deep in-the-funnel prospects fast answers, connections to real people and the type of detailed information that plays an important role in high-consideration purchases.

Call analytics platforms have become important tools to help marketers identify and activate the rich data hidden in the growing volume of inbound calls. Call analytics platforms track both online and offline leads, following a call from its source (i.e., website, social media and click-to-call search or display ads) to a sales representative (i.e., based on geographic location or product line and on to a conversion or lack thereof).

The ability to track calls is a core use case of call analytics technology. However, advances in machine learning and artificial intelligence (AI) are driving more sophisticated applications, including the following:

  • First-party database-building: As marketers lose access to third-party cookie data, first-party data sources such as phone calls are becoming more valuable in brand efforts to build privacy-compliant customer databases. Call analytics platforms facilitate the scaled collection and analysis of caller data.
  • Customer journey attribution: Call analytics platforms provide online-to-offline attribution across media channels, helping marketers understand the role that each customer touchpoint plays in a conversion. The result is more efficient resource allocation and more relevant messaging based on customer preferences.
  • Marketing campaign optimization: Call analytics platforms connect calls to the search keywords, social display ads or webpages that drove them. Marketers can use unique phone numbers for each website visitor to understand which pages and elements are driving the highest quality calls, as well as which ones are causing visitors to leave. Call data, including demographics, product interests and buying stage, can also be used to optimize search bids or make on-the-fly changes to campaign messaging and creative.
  • Audience segmentation and targeting: Call analytics platforms record and transcribe calls, then apply AI-based models to the results to determine the characteristics of the highest-performing callers or leads. Using the data, marketers can build personas or look-alike audiences to create high-performing customer segments.
  • Personalized, intelligent lead routing: Call analytics platforms use machine learning to score and route calls based on factors including call source, geography, demographics, purchase history or intent. Tools such as whisper messages arm sales reps with known customer information that personalizes the caller experience.
  • Sales rep coaching and development: Many call analytics platforms include automated sales performance and evaluation tools to provide scoring/grading systems, script optimization and real-time alerts that flag lost opportunities.
  • Integrations with chat applications and SMS messaging: Like phone calls, online chat and messaging are key channels for customers to interact with businesses, so some players are extending their experience with conversational analysis to popular messaging apps as well as site-specific chat and SMS.

Core capabilities of call analytics platforms

Most platforms offer a core set of capabilities focused on call tracking, recording, scoring, routing and fraud prevention. Dynamic number insertion (DNI) is used to enable marketers to assign unique phone numbers to different digital marketing campaigns in order to track the source of an inbound call. When a consumer clicks through to a site from an online ad, DNI technology displays the phone number that’s unique to the specific search engine, webpage, keyword or another source. Vendors offer DNI by call source, online session or URL. The ubiquity of mobile calls to businesses has led to increased demand for local numbers or extensions that are dynamically generated based upon the consumer’s location, without jeopardizing the accuracy of name-address-phone (NAP) information for SEO purposes.

Call fraud prevention is another important feature, as automated dialers, fax machines and even computer programmers can hack into carrier networks to fraudulently inflate call volumes and revenue for pay-per-call services. In response, vendors have developed proprietary call fraud detection and prevention tools that identify, monitor and block suspicious call patterns and routes.

Vendors begin to differentiate their platforms by offering more advanced capabilities, often requiring additional investment, which include – but are not limited to – the following.

Multichannel attribution

Most call analytics platforms offer some level of call tracking that enables users to attribute the source of a call back to a specific ad, keyword or webpage. By tracking inbound calls from their sources, call analytics platforms provide an important link between online and offline channels, and allow marketers to more accurately measure the ROI of their multichannel marketing campaigns. Some vendors are offering more sophisticated attribution tools that can identify call sources beyond search – including native social ads and display ads that don’t include a click-to-call button. The goal is to more effectively allocate spending across marketing channels, and establish a more accurate link between digital campaigns and offline conversions.

AI-driven speech analytics

Call analytics technology has evolved from providing basic analytics to providing “conversation intelligence” based on AI-driven algorithms that extract and predict caller intent, and measure caller tone, sentiment and emotion. AI is increasingly being applied to analyze and “spot” keywords, phrases and speech patterns for positive or negative signals of conversion intent.

These signals can also include the length of time a caller speaks versus how long the sales rep speaks. Many call analytics platforms use a variety of natural language processing (NLP) and machine-learning algorithms to automatically assess calls and score leads. The results can be used immediately to help sales reps on the call by using whisper messages heard through the rep’s headset to influence call outcomes. The data can also be used post-call to feed CRM systems and trigger nurturing campaigns.

Intelligent call scoring/routing

Machine learning-based or “intelligent” lead scoring and routing systems are now being used to optimally route a call to the rep or location most qualified to close a sale or other conversion action (i.e., make an appointment). These types of scoring and routing tools automatically qualify and distribute calls to the appropriate sales reps or departments based on variables such as caller source (i.e., website, social media, search ad), geography, demographics (i.e., age, gender, income) or intent. Some of the tools used in intelligent call scoring and routing include interactive voice response (IVR), which prequalifies callers before they are routed to a rep through a short series of automated questions, and whisper messages that alert reps to relevant caller data before they pick up the call. Calls can be tracked through the system to follow conversions and other qualifying events.

Native social analytics integration

Call analytics platform vendors are leveraging the growth in native social advertising and click-to-call to more seamlessly integrate social media and call analytics. Most vendors offer Facebook and Instagram call tracking to attribute calls back to social media ads.

Several vendors also use Facebook’s offline conversion API to integrate their call data directly into Facebook ad campaigns through the Facebook Ads Manager.

Chat and messaging integrations and analytics

Chat applications — either mainstream messengers like Facebook Messenger or WhatsApp, or chat functionality on websites — have become key channels for customer service and pre-sales inquiries. Additionally, many such interactions are now enabled by SMS. Some call analytics vendors incorporate connections and data gathering from these sources, to give marketers a more holistic view of customer interactions and sentiments.


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Sales rep coaching/evaluation

Several call analytics platforms are rooted in sales coaching and evaluation, and use call recording tools to maximize efficiency in the call center and among sales staffs. Today, the platforms provide machine learning-based call handling analytics tools that assess location and/or rep performance, and provide scoring/grading systems, script optimization and real-time alerts that flag lost opportunities.

Data privacy compliance

Call data privacy continues to be a priority, particularly for businesses in the healthcare and financial services markets, which must comply with HIPAA and HITECH regulations and the CCPA. U.S.-based marketers with European prospects or customers are subject to the European Union’s GDPR. Many vendors automatically redact personally identifiable information (PII) and consumer financial information from call recordings and transcripts to conform to the PCI DSS.

Martech ecosystem integration

Integrating call analytics data with martech and ad tech software systems has become essential to creating a unified view of callers, webpage and store visitors, prospects and customers. Call analytics vendors have expanded the number of built-in or native integrations available with SEO, PPC, DSP, CRM and marketing automation systems, as marketers try to create a more seamless customer experience across all touchpoints. In particular, calls play an important role in establishing the link between digital and offline channels. To that end, call analytics platform vendors continue to expand their connectivity with social media, Google and Bing, analytics tools, affiliate marketers and digital agencies. Most vendors also offer APIs to facilitate importing and exporting third-party data from external marketing and advertising systems. Access to these APIs may or may not be included in base pricing.


What is call analytics and what does it do for

Explore platform capabilities from vendors like CallRail, Invoca, CallSource, DialogueTech and more in the full MarTech Intelligence Report on enterprise call analytics platforms.

Click here to download!


The benefits of using call analytics platforms

Call tracking and analytics play a vital role in bridging the gap between online and offline channels, leading to more efficient marketing resource allocation and improved sales staff effectiveness. The specific benefits of using an enterprise call analytics platform include – but are not limited to – the following:

  • Improved multichannel attribution. By using DNI to track inbound calls to their source, call analytics establish the link between inbound calls and online search, display, social or email campaigns. The data can be fed into attribution models for greater accuracy.
  • More unified customer view. Integrating call analytics data with CRM, marketing automation, tag management and other martech or ad tech systems provides the enterprise with a more complete view of each prospect and customer enabling more relevant, personalized marketing.
  • Optimized marketing campaigns. Inbound calls can be tracked to their marketing source at the keyword, session, campaign or channel levels, and followed through the conversion funnel to identify the most profitable sources. Campaigns can then be optimized to focus on the messages and sources that attract the highest quality calls.
  • Smarter marketing resource allocation. Understanding which ads, keywords and web pages drive the most profitable calls leads to more informed marketing and media spend decisions.
  • Increased sales staff productivity. Tools such as IVR and intelligent call routing send high-value leads to the right agents or locations to close sales more efficiently. Call analytics can also reveal inefficiencies that, when improved, can boost key metrics such as lost opportunities.
  • Better sales performance. Call analytics platforms record and analyze inbound calls to identify which agents and sales techniques close the most sales. Training can be provided to improve results, where necessary. Whisper messages help agents customize their approaches based on known customer information during calls.

About The Author

Does your marketing team need a digital experience platform DXP

Pamela Parker is Research Director at Third Door Media’s Content Studio, where she produces MarTech Intelligence Reports and other in-depth content for digital marketers in conjunction with Search Engine Land and MarTech. Prior to taking on this role at TDM, she served as Content Manager, Senior Editor and Executive Features Editor. Parker is a well-respected authority on digital marketing, having reported and written on the subject since its beginning. She’s a former managing editor of ClickZ and has also worked on the business side helping independent publishers monetize their sites at Federated Media Publishing. Parker earned a master’s degree in journalism from Columbia University.


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How Does Success of Your Business Depend on Choosing Type of Native Advertising?

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How Does Success of Your Business Depend on Choosing Type of Native Advertising?

The very first commercial advertisement was shown on TV in 1941. It was only 10 seconds long and had an audience of 4,000 people. However, it became a strong trigger for rapid advertising development. The second half of the 20th century is known as the golden age of advertising until the Internet came to the forefront and entirely transformed the advertising landscape. The first commercial banner appeared in the mid-90s, then it was followed by pop-ups, pay-by-placement and paid-pay-click ads. Companies also started advertising their brands and adding their business logo designs, which contributes to consumer trust and trustworthiness.

The rise of social media in the mid-2000s opened a new dimension for advertising content to be integrated. The marketers were forced to make the ads less intrusive and more organic to attract younger users. This is how native advertising was born. This approach remains a perfect medium for goods and services promotion. Let’s see why and how native ads can become a win-win strategy for your business.

What is native advertising?

When it comes to digital marketing, every marketer talks about native advertising. What is the difference between traditional and native ones? You will not miss basic ads as they are typically promotional and gimmicky, while native advertising naturally blends into the content. The primary purpose of native ads is to create content that resonates with audience expectations and encourages users to perceive it seamlessly and harmoniously.

Simply put, native advertising is a paid media ad that organically aligns with the visual and operational features of the media format in which it appears. The concept is quite straightforward: while people just look through banner ads, they genuinely engage with native ads and read them. You may find a lot of native ads on Facebook, Twitter and Instagram – they appear in the form of “in-feed” posts that engage users in search for more stories, opinions, goods and services. This unobtrusive approach turns native ads into a powerful booster for any brand.

How does native advertising benefit your business?

An average Internet user comes across around 10,000 ads a day. But even physically, it is impossible to perceive this amount of information in 24 hours. So, most of them use adblockers, nullifying all efforts of markers. Native ads successfully overcome this digital challenge thanks to their authenticity. And this is not the only advantage of native advertising. How else does your business benefit? Here are just a few major benefits that prove the value of native ads:

Better brand awareness. Native ads contribute to the brand’s visibility. They seamlessly blend into educational, emotional, and visual types of content that can easily become viral. While promotional content typically receives limited shares, users readily share valuable or entertaining content. Consequently, while you incur expenses only for the display of native ads, your audience may go the extra mile by sharing your content and organically promoting your brand or SaaS product at no additional cost.

Increased click-through rates. Native ads can generate a thrilling click-through rate (CTR) primarily because they are meticulously content-adaptable. Thus, native ads become an integral part of the user’s journey without disrupting their browsing experience. Regardless of whether your native advertising campaign is designed to build an audience or drive specific actions, compelling content will always entice users to click through.

Cost-efficient campaign performance. Native advertising proves to be cheaper compared to a traditional ad format. It mainly stems from a higher CTR. Thanks to precise targeting and less customer resistance, native ads allow to bring down cost-per-click.

Native ads are continuously evolving, enabling marketers to experiment with different formats and use them for successful multi-channel campaigns and global reach.

Types of native advertising

Any content can become native advertising as there are no strict format restrictions. For example, it can be an article rating the best fitness applications, an equipment review, or a post by an influencer on a microblog. The same refers to the channels – native ads can be placed on regular websites and social media feeds. Still, some forms tend to be most frequently used.

  • In-feed ads. This type of ad appears within the content feed. You have definitely seen such posts on Facebook and Instagram or such videos on TikTok. They look like regular content but are tagged with an advertising label. The user sees these native ads when scrolling the feed on social media platforms.
  • Paid search ads. These are native ads that are displayed on the top and bottom of the search engine results page. They always match user’s queries and aim to capture their attention at the moment of a particular search and generate leads and conversions. This type of ad is effective for big search platforms with substantial traffic.
  • Recommendation widgets. These come in the form of either texts or images and can be found at the end of the page or on a website’s sidebar. Widgets offer related or intriguing content from either the same publisher or similar sources. This type of native ads is great for retargeting campaigns.
  • Sponsored content. This is one of the most popular types of native advertising. Within this format, an advertiser sponsors the creation of an article or content that aligns with the interests and values of the platform’s audience. They can be marked as “sponsored” or “recommended” to help users differentiate them from organic content.
  • Influencer Advertising. In this case, advertisers partner with popular bloggers or celebrities to gain the attention and trust of the audience. Influencers integrate a product, service, or event into their content or create custom content that matches their style and topic.

Each of these formats can bring stunning results if your native ads are relevant and provide value to users. Use a creative automation platform like Creatopy to design effective ads for your business.

How to create a workable native ad?

Consider these 5 steps for creating a successful native advertising campaign:

  • Define your target audienceUsers will always ignore all ads that are not relevant to them. Unwanted ads are frustrating and can even harm your brand. If you run a store for pets, make sure your ads show content that will be interesting for pet owners. Otherwise, the whole campaign will be undermined. Regular market research and data analysis will help you refine your audience and its demographics.
  • Set your goals. Each advertising campaign should have a clear-cut objective. Without well-defined goals, it is a waste of money. It is a must to know what you want to achieve – introduce your brand, boost sales or increase your audience.
  • Select the proper channels. Now, you need to determine how you will reach out to your customers. Consider displaying ads on social media platforms, targeting search engine result pages (SERPs), distributing paid articles, or utilizing in-ad units on different websites. You may even be able to get creative and use email or SMS in a less salesy and more “native”-feeling way—you can find samples of texts online to help give you ideas. Exploring demand side platforms (DSP) can also bring good results.
  • Offer compelling content. Do not underestimate the quality of the content for your native ads. Besides being expertly written, it must ideally match the style and language of the chosen channel,whether you’re promoting professional headshots, pet products, or anything else. The main distinctive feature of native advertising is that it should fit naturally within the natural content.
  • Track your campaign. After the launch of native ads, it is crucial to monitor the progress, evaluating the costs spent and results. Use tools that help you gain insights beyond standard KPIs like CTR and CPC. You should get engagement metrics, customer data, campaign data, and third-party activity data for further campaign management.

Key takeaway

Summing up the above, it is time to embrace native advertising if you haven’t done it yet. Native ads seamlessly blend with organic content across various platforms, yielding superior engagement and conversion rates compared to traditional display ads. Marketers are allocating higher budgets to native ads because this format proves to be more and more effective – content that adds value can successfully deal with ad fatigue. Native advertising is experiencing a surge in popularity, and it is to reach its peak. So, do not miss a chance to grow your business with the power of native ads.or you can do digital marketing course from Digital Vidya.

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OpenAI’s Drama Should Teach Marketers These 2 Lessons

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OpenAI’s Drama Should Teach Marketers These 2 Lessons

A week or so ago, the extraordinary drama happening at OpenAI filled news feeds.

No need to get into all the saga’s details, as every publication seems to have covered it. We’re just waiting for someone to put together a video montage scored to the Game of Thrones music.

But as Sam Altman takes back the reigns of the company he helped to found, the existing board begins to disintegrate before your very eyes, and everyone agrees something spooked everybody, a question arises: Should you care?

Does OpenAI’s drama have any demonstrable implications for marketers integrating generative AI into their marketing strategies?

Watch CMI’s chief strategy advisor Robert Rose explain (and give a shoutout to Sutton’s pants rage on The Real Housewives of Beverly Hills), or keep reading his thoughts:

For those who spent last week figuring out what to put on your holiday table and missed every AI headline, here’s a brief version of what happened. OpenAI – the huge startup and creator of ChatGPT – went through dramatic events. Its board fired the mercurial CEO Sam Altman. Then, the 38-year-old entrepreneur accepted a job at Microsoft but returned to OpenAI a day later.

We won’t give a hot take on what it means for the startup world, board governance, or the tension between AI safety and Silicon Valley capitalism. Rather, we see some interesting things for marketers to put into perspective about how AI should fit into your overall content and marketing plans in the new year.

Robert highlights two takeaways from the OpenAI debacle – a drama that has yet to reach its final chapter: 1. The right structure and governance matters, and 2. Big platforms don’t become antifragile just because they’re big.

Let’s have Robert explain.

The right structure and governance matters

OpenAI’s structure may be key to the drama. OpenAI has a bizarre corporate governance framework. The board of directors controls a nonprofit called OpenAI. That nonprofit created a capped for-profit subsidiary – OpenAI GP LLC. The majority owner of that for-profit is OpenAI Global LLC, another for-profit company. The nonprofit works for the benefit of the world with a for-profit arm.

That seems like an earnest approach, given AI tech’s big and disruptive power. But it provides so many weird governance issues, including that the nonprofit board, which controls everything, has no duty to maximize profit. What could go wrong?

That’s why marketers should know more about the organizations behind the generative AI tools they use or are considering.

First, know your providers of generative AI software and services are all exploring the topics of governance and safety. Microsoft, Google, Anthropic, and others won’t have their internal debates erupt in public fireworks. Still, governance and management of safety over profits remains a big topic for them. You should be aware of how they approach those topics as you license solutions from them.

Second, recognize the productive use of generative AI is a content strategy and governance challenge, not a technology challenge. If you don’t solve the governance and cross-functional uses of the generative AI platforms you buy, you will run into big problems with its cross-functional, cross-siloed use. 

Big platforms do not become antifragile just because they’re big

Nicholas Taleb wrote a wonderful book, Antifragile: Things That Gain From Disorder. It explores how an antifragile structure doesn’t just withstand a shock; it actually improves because of a disruption or shock. It doesn’t just survive a big disruptive event; it gets stronger because of it.

It’s hard to imagine a company the size and scale of OpenAI could self-correct or even disappear tomorrow. But it can and does happen. And unfortunately, too many businesses build their strategies on that rented land.

In OpenAI’s recent case, the for-profit software won the day. But make no bones about that victory; the event wasn’t good for the company. If it bounces back, it won’t be stronger because of the debacle.

With that win on the for-profit side, hundreds, if not thousands, of generative AI startups breathed an audible sigh of relief. But a few moments later, they screamed “pivot” (in their best imitation of Ross from Friends instructing Chandler and Rachel to move a couch.)

They now realize the fragility of their software because it relies on OpenAI’s existence or willingness to provide the software. Imagine what could have happened if the OpenAI board had won their fight and, in the name of safety, simply killed any paid access to the API or the ability to build business models on top of it.

The last two weeks have done nothing to clear the already muddy waters encountered by companies and their plans to integrate generative AI solutions. Going forward, though, think about the issues when acquiring new generative AI software. Ask about how the vendor’s infrastructure is housed and identify the risks involved. And, if OpenAI expands its enterprise capabilities, consider the implications. What extra features will the off-the-shelf solutions provide? Do you need them? Will OpenAI become the Microsoft Office of your AI infrastructure?

Why you should care

With the voluminous media coverage of Open AI’s drama, you likely will see pushback on generative AI. In my social feeds, many marketers say they’re tired of the corporate soap opera that is irrelevant to their work.

They are half right. What Sam said and how Ilya responded, heart emojis, and how much the Twitch guy got for three days of work are fodder for the Netflix series sure to emerge. (Robert’s money is on Michael Cera starring.)

They’re wrong about its relevance to marketing. They must be experiencing attentional bias – paying more attention to some elements of the big event and ignoring others. OpenAI’s struggle is entertaining, no doubt. You’re glued to the drama. But understanding what happened with the events directly relates to your ability to manage similar ones successfully. That’s the part you need to get right.

Want more content marketing tips, insights, and examples? Subscribe to workday or weekly emails from CMI.

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Cover image by Joseph Kalinowski/Content Marketing Institute

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The Complete Guide to Becoming an Authentic Thought Leader

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The Complete Guide to Becoming an Authentic Thought Leader

Introduce your processes: If you’ve streamlined a particular process, share it. It could be the solution someone else is looking for.

Jump on trends and news: If there’s a hot topic or emerging trend, offer your unique perspective.

Share industry insights: Attended a webinar or podcast that offered valuable insights. Summarize the key takeaways and how they can be applied.

Share your successes: Write about strategies that have worked exceptionally well for you. Your audience will appreciate the proven advice. For example, I shared the process I used to help a former client rank for a keyword with over 2.2 million monthly searches.

Question outdated strategies: If you see a strategy that’s losing steam, suggest alternatives based on your experience and data.

5. Establish communication channels (How)

Once you know who your audience is and what they want to hear, the next step is figuring out how to reach them. Here’s how:

Choose the right platforms: You don’t need to have a presence on every social media platform. Pick two platforms where your audience hangs out and create content for that platform. For example, I’m active on LinkedIn and X because my target audience (SEOs, B2B SaaS, and marketers) is active on these platforms.

Repurpose content: Don’t limit yourself to just one type of content. Consider repurposing your content on Quora, Reddit, or even in webinars and podcasts. This increases your reach and reinforces your message.

Follow Your audience: Go where your audience goes. If they’re active on X, that’s where you should be posting. If they frequent industry webinars, consider becoming a guest on these webinars.

Daily vs. In-depth content: Balance is key. Use social media for daily tips and insights, and reserve your blog for more comprehensive guides and articles.

Network with influencers: Your audience is likely following other experts in the field. Engaging with these influencers puts your content in front of a like-minded audience. I try to spend 30 minutes to an hour daily engaging with content on X and LinkedIn. This is the best way to build a relationship so you’re not a complete stranger when you DM privately.

6. Think of thought leadership as part of your content marketing efforts

As with other content efforts, thought leadership doesn’t exist in a vacuum. It thrives when woven into a cohesive content marketing strategy. By aligning individual authority with your brand, you amplify the credibility of both.

Think of it as top-of-the-funnel content to:

  • Build awareness about your brand

  • Highlight the problems you solve

  • Demonstrate expertise by platforming experts within the company who deliver solutions

Consider the user journey. An individual enters at the top through a social media post, podcast, or blog post. Intrigued, they want to learn more about you and either search your name on Google or social media. If they like what they see, they might visit your website, and if the information fits their needs, they move from passive readers to active prospects in your sales pipeline.

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