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What is marketing automation?

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What is marketing automation?

Marketing automation software can improve marketing productivity and increase lead quality. Here’s what you need to know before adopting a marketing automation platform.

Marketing automation is the use of software and web-based services to execute, manage and automate repetitive marketing tasks and processes to more effectively market through multiple channels (i.e., email, mobile, social media, and websites). Marketing automation focuses on the definition, scheduling, segmentation and tracking of marketing campaigns, allowing the marketing and sales organizations to nurture leads with highly personalized content aimed at attracting and retaining customers.

Today, marketing automation is one of the core activities of a marketing department — whether for a small local business or a large consumer or B2B enterprise. But the platforms that power these activities continue to evolve.

Estimated reading time: 13 minutes


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What is marketing automation?

Investments in marketing technology continue to be a priority for businesses across the board, as they strive to meet increased demands for personalization and a need to collect, authenticate and analyze rapidly increasing amounts of consumer data to improve the customer experience (CX). For B2B players, this often means using a marketing automation platform.

Most marketing automation solutions provide tools for email campaign development and execution (including landing pages), as well as lead capture, scoring and nurturing. The platforms also typically provide centralized marketing databases and a basic level of reporting on web traffic, visitor behavior and campaign results.

Combined, the core features offered by most marketing automation platforms profiled in this report include:

  • Email marketing and landing page development;
  • Lead management (i.e., capture, scoring and nurturing);
  • Native CRM integration; and
  • APIs or app marketplaces for faster martech system access.

The more basic functions of marketing automation have become somewhat commoditized, so platform vendors mostly look to differentiate their offerings based on the ability to scale (especially to new marketing channels), usability, ease of implementation and customer experience features. One area growing especially quickly involves the use of artificial intelligence and machine learning to suggest audiences or messaging.

Platform vendors are also looking to differentiate themselves by offering more support for increasingly sophisticated customers who have adopted the software and who are looking to justify the investment by proving ROI.

All of this means market is quickly evolving, as marketers demand integrated marketing functionality that rapidly translates into bottom-line return. Vendors continue to add more advanced features to provide marketing end-users with the ability to build, track and manage campaigns across channels and/or devices, and monitor the flow of leads as they move from marketing to sales.

These features include, but are not limited to:

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  • Dynamic content generation (email, landing pages and/or website);
  • Email deliverability tools;
  • Account-based marketing (ABM);
  • Mobile marketing;
  • AI-based predictive analytics; and
  • Social/lead profile integration.

Dynamic content generation

Virtually all marketing automation platforms provide the ability to create, send and measure personalized email campaigns. Where they differ is in how email, landing page and website content created and personalized. Some vendors offer wizard-based campaign design or content templates, while others provide a more customized approach.

There are also differences in static vs. dynamically generated content, which adjusts on the fly as prospects interact with a website or form. Progressive profiling is often offered to pre-populate forms with known data and uses a drip approach to capture additional prospect information each time they interact with campaigns.

Message deliverability is also an important factor to consider. Some B2B marketing automation vendors offer dedicated IP addresses to improve deliverability, and/or monitor deliverability by including their own email deliverability services or those from partners. Email previewing is an advanced function but may be critical to marketers that want to reach their audience through mobile devices and see what their message will look like on smaller screens.

The market is quickly evolving, as modern marketers demand integrated marketing functionality that rapidly translates into bottom-line return.


Why data driven decision making is the foundation of successful CX

New features are making marketing automation platforms more powerful than ever. Learn about trends and capabilities of marketing automation software in the latest edition of this MarTech Intelligence Report.

Click here to download!


Lead management

Lead management comprises three functions: lead capture, lead scoring and lead nurturing. Leads are captured from a variety of sources that feed the marketing automation database, including (but not limited to) website visitors, social media, paid digital campaigns, email marketing respondents, trade show attendees and purchased third-party lists. Tools will vary based on the ease with which additional lead sources can be captured, such as through an open API, or whether the software offers landing page optimization.

Lead scoring assigns a value to each lead based on a predetermined set of rules or criteria. Traditional lead scoring models are generally based on two sets of data values: behavior (i.e., site purchases, browsing, social posts) and demographics/firmographics. Many digital marketing automation tools now offer predictive scoring driven by machine learning, which can incorporate hundreds of data points by sourcing websites, social networks and internal systems such as the CRM and marketing database itself to calculate scores.

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Lead nurturing is the process of keeping prospects engaged with the brand through periodic, personalized communications or campaigns until they are ready to buy. Marketing automation software may offer a number of pre-built nurturing steps or actions, as well as allow users to customize their content and process. These efforts are meant to build a relationship between the brand and its prospects, and drive interaction with sales if and when the prospect is ready.

Predictive analytics

Virtually all of the marketing automation platforms profiled in this report provide a standard set of analytics that track quantifiable data such as website visitor activity, pages viewed, time spent on site, emails opened, content downloaded and campaign responses. More vendors are offering predictive analytics and models based on machine learning, which uses algorithms to process data and surface trends or insights that enable marketers to customize visitor experiences and marketing campaigns.

Several platforms have invested in artificial intelligence (AI) to go a step beyond machine learning and use technology to “mimic” human intelligence and recommend marketing actions or outcomes. These may include highly personalized website content or product recommendations based on analysis of consumption trends, on-site behavior, firmographics and CRM data. Other vendors rely on plug-and-play integration with predictive analytics tools to offer greater analytics and personalization capabilities.

Mobile marketing automation

Creating an engaging experience for mobile prospects and customers is a must-have capability. As a result, many B2B marketing automation software include responsive templates for email, landing pages and web forms. Several vendors integrate with email testing tools such as Litmus, to allow users to preview email marketing messages across email clients and devices.

More advanced mobile marketing features include SMS/texting, in-app marketing and remote platform management from mobile devices. In-app marketing features can include “push” notifications or ads based on geography (i.e., geo-fencing or beaconing) or during events. Marketing automation vendors have also expanded platform access to mobile users, moving beyond automated alerts and remote data collection to full platform management.

Most marketing automation software profiled in this report provide a standard set of analytics that track quantifiable data such as website visitor activity, pages viewed, time spent on site, emails opened, content downloaded and campaign responses.

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Lead nurturing is the process of keeping prospects engaged with the brand through periodic, personalized communications or campaigns until they are ready to buy.

Account-based marketing (ABM)

Aligning marketing initiatives with sales teams has become a leading account-based marketing (ABM) priority for marketers. The goal is to target marketing programs to prospect or customer buying teams, rather than individuals (who may have moved into new positions or firms.) Most of the time, a B2B buyer is not a single person but a buying group. The larger the purchase, the more people and departments are involved. Marketing automation vendors continue to add new ABM features to their platforms to enable marketers to address the buying group as well as individual members, including enhanced account nurturing and predictive scoring capabilities.

Social/lead profile integration

Most of the B2B digital marketing automation vendors profiled in this report provide some level of social media publishing, sharing and tracking within the platform for networks such as Facebook, Instagram, Twitter and LinkedIn. Some platforms provide more advanced social media tools to monitor social posts and add social behavior to lead profiles, often using social engagement as a scoring factor. Other platforms enable the use of social media sign-on to capture social profile data and build lead profiles.

Native CRM integration

With more businesses seeking to align marketing with sales, native or out-of-the-box integration with CRM systems has become a critical feature for marketing automation systems. Salesforce, Microsoft Dynamics 365, Oracle NetSuite and SugarCRM are some of the most commonly available connectors.

Data is synchronized between the two systems and shared in both directions at frequent intervals. For example, data that is added by a sales rep to an account record in the CRM will be automatically added to the record in the marketing automation tool for marketing end-users to view and act upon, as well.

Third-party software connectivity

B2B marketing automation vendors continue to open their platform architectures through APIs and app marketplaces to offer customers access to an expansive array of third-party software systems. The app marketplaces provide faster “plug-and-play” access between the systems, although there may be additional fees to purchase the marketplace apps.

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If a preferred app is not available on a digital marketing automation vendor’s marketplace it doesn’t mean that the two systems won’t connect – it means that some customization will be required. API use does incur additional charges, generally on a per-call basis for each data download

Proactive recommendations based on AI

Martech vendors in many categories, including B2B marketing automation, are working to incorporate functionality that smooths the workflow for marketers using their software. One significant focus is providing users with proactive recommendations or suggestions for best next steps based on aggregated data and historical usage patterns.

Why do you need a marketing automation platform?

Marketers at companies of all sizes can gain these benefits from a marketing automation platform:

  • Increased marketing efficiency. Automating time-consuming, manual tasks around content creation, management and personalization; campaign scheduling and execution; data hygiene (i.e. duplicate or inconsistent data residing in various silos); communication with sales; and lead nurturing saves time and improves productivity.
  • Enhanced ability to generate more and better qualified leads. Marketing automation can combine multiple criteria, including demographic, firmographic and behavioral data (pages visited, downloads, filled out forms) with a lead scoring system to generate and identify sales-qualified leads.
  • A multichannel view of prospect behavior. Today’s digital marketing automation platforms are integrating multiple channels and devices – including social media and mobile — to create more comprehensive prospect profiles and holistic views of prospect behavior.
  • Better alignment of sales and marketing goals. Marketing automation software can help align sales and marketing efforts to ensure that sales reps are working with sales-ready leads. By working cooperatively to set scoring parameters and define qualified leads, sales and marketing become one team. Marketing works on building relationships with early stage leads to enable sales to focus their efforts on the most highly qualified prospects.
  • Improved lead conversion and ROI. Numerous studies have found that using a marketing automation system can increase conversions. Forrester found that B2B marketers implementing marketing automation experience a 10% increase in their sales-pipeline contribution. Marketing automation can result in a 15% increase in sales productivity as well as a 12% decrease in marketing overhead, according to tech research firm Nucleus Research.

What is Marketo

Explore marketing automation solutions from vendors like Marketo, HubSpot, Salesforce and more in the full MarTech Intelligence Report on marketing automation platforms.

Click here to download!


The role of marketing automation platforms

In May of 2019, Forrester’s Laura Cross, VP and principal analyst for demand- and account-based marketing, speculated that MAPs have “not evolved to keep up with the needs of the modern demand marketer.” Indeed, marketing automation platforms are so well-established as to be rarely discussed. For example, it’s difficult to find independent projections on marketing automation spend, with the latest numbers from Forrester projecting global spend to reach $25.1 billion by 2023, up from $11.4 billion in 2017. However, that was published in April of 2018 as its Marketing Automation Technology Forecast, 2017-2023.

As of yet, though, there’s no sign of marketing automation platforms going extinct. However, companies in the MAP category expanding into areas like “multimedia marketing hubs” or “CRM lead management” or “account-based marketing.” Notably, marketing automation platforms had no spot at all on Gartner’s Hype Cycle for Digital Marketing, 2021. Could this be because it has already transitioned to what Gartner calls the “plateau of productivity”?

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Where marketing automation providers seem to be giving up a little bit of territory is from customer data plaforms, which are sometimes taking over the data management and audience segmentation tasks previously handled by MAPs.

At the same time, these CDPs also still feature integrations with marketing automation platforms because they still perform functions that other systems lack.

Will CDP’s replace marketing automation platforms?

The must-have, much-hyped customer data platform (CDP) appears to have its eyes on B2B marketers, promising to handle vast amounts of data to deliver highly-personalized customer experiences. 

Adobe’s Real-time CDP announced new features aimed at B2B brands in November 2020, which include a pre-built connector to its B2B Marketing Automation Platform, Marketo Engage. Dun & Bradstreet, with its D&B Lattice CDP, also understandably has a primarily B2B focus.

Though CDP platforms are still relatively new, adoption has been rapid and these tools could eventually pose a threat to marketing automation platforms as they provide some of the same tools and functionalities.

Who’s who in B2B Marketing Automation: The vendor landscape

The enterprise B2B marketing automation market is concentrated among a few cloud vendors, including Salesforce, Oracle and Adobe. Acquisitions by these players aimed at consolidating their positions at the top of the market have now been largely integrated.

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Oracle made its acquisition of Eloqua in December 2012, becoming the first to add this capability to its offerings. Salesforce followed by adding Pardot in 2013 when it acquired ExactTarget, which had purchased Pardot the year before. The foundation of Adobe’s capabilities in the space is its 2018 purchase of rival marketing automation platform Marketo for $4.72 billion. It had previously bought Magento Commerce for $1.68 billion.

2019 saw a great deal of action in the space. The year saw Acoustic formed as a standalone company after IBM spun off its Watson Marketing operation. IBM’s Unica marketing automation platform went to HCL Technologies that year.

Among independent martech providers that year, we saw the acquisition of Mautic by open-source cloud platform Acquia for an undisclosed sum in May of 2019, only to have the parent purchased by Vista Partners in September for $1B. Also in May, SugarCRM picked up Salesfusion and re-branded it Sugar Market, in a deal in which terms were not publicly disclosed.

The pandemic year of 2020 saw acquisitions of smaller players, for the most part. CRM company Pipedrive purchased Mailigen for an undisclosed sum in March of 2020. Facebook picked up Kustomer, largely described as a CRM firm but also boasting messaging automation functionality, in November 2020 for a reported $1 billion.

December 2020 saw marketing automation/attribution player Springbot acquire Matcha, giving it content management capabilities. Meanwhile, Thryv Holdings acquired Melbourne, Australia-based Sensis in March 2020, rebranding it as Thryv in September 2021.

Date Transactions
2021 – Maropost acquires e-commerce platform Neto in March 2021 for $60M plus additional consideration,
subsequently rebranding the platform Maropost Commerce Cloud.
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– Constant Contact purchases SharpSpring for $240M, adding to its stable of offerings for SMBs.

– ActiveCampaign raises $240M in Series C funding that values it at more than $3B, following a 2020 round of $100M. The company says it plans to invest in product development, expansion and building its partner ecosystem.

2020 – Springbot buys Matcha. Deal terms weren’t disclosed.

– Facebook acquires Kustomer for a reported $1B.

– Pipedrive buys Mailigen for an undisclosed sum. Thryv Holdings buys Sensis for $200M,
later rebranding it as Thryv.

2019 – Acquia acquires Mautic (terms not disclosed). Vista Equity Partners later (Sept 2019) buys Acquia for $1B
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– SugarCRM buys Salesfusion (undisclosed amount); rebrands it to Sugar Market. The acquisition followed the company’s buy of Collabspot and preceded its purchase of Corvana. These units are now called Sugar Connect and Sugar Discover, respectively.

– Mailchimp acquires Sawa (undisclosed sum)

– Infusionsoft rebrands as Keap; launches CRM

– j2Global acquires iContact for $49M

2018 – Salesforce acquires Rebel (undisclosed sum)

– Infusionsoft (now known as Keap) secures $20M in Series E funding led by ORIX USA Corp.

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– Adobe acquires Marketo for $4.75B

Salesforce acquires Datorama for $800M

– Adobe acquires Magneto Commerce for $1.68B

– Salesforce acquires Mulesoft $6.5B and CloudCraze (undisclosed sum)

Source: Third Door Media, Crunchbase

There will likely be more acquisitions and positioning shifts to come, as marketing automation capabilities are combined with categories like CRM, lead management and campaign automation.

The consolidation kept coming in 2021, with Maropost acquiring e-commerce platform Neto in March 2021 for $60M plus additional consideration, subsequently rebranding the platform Maropost Commerce Cloud. In September, Constant Contact purchased SharpSpring, adding to its stable of offerings for SMBs.

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Get the in-depth scoop on B2B Marketing Automation in our buyer’s guide. Download it now!

 


About The Author

1641869137 309 Does your marketing team need an SEO platform

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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Should Your Brand Shout Its AI and Marketing Plan to the World?

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Should Your Brand Shout Its AI and Marketing Plan to the World?

To use AI or not to use AI, that is the question.

Let’s hope things work out better for you than they did for Shakespeare’s mad Danish prince with daddy issues.

But let’s add a twist to that existential question.

CMI’s chief strategy officer, Robert Rose, shares what marketers should really contemplate. Watch the video or read on to discover what he says:

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Should you not use AI and be proud of not using it? Dove Beauty did that last week.

Should you use it but keep it a secret? Sports Illustrated did that last year.

Should you use AI and be vocal about using it? Agency giant Brandtech Group picked up the all-in vibe.

Should you not use it but tell everybody you are? The new term “AI washing” is hitting everywhere.

What’s the best option? Let’s explore.

Dove tells all it won’t use AI

Last week, Dove, the beauty brand celebrating 20 years of its Campaign for Real Beauty, pledged it would NEVER use AI in visual communication to portray real people.

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In the announcement, they said they will create “Real Beauty Prompt Guidelines” that people can use to create images representing all types of physical beauty through popular generative AI programs. The prompt they picked for the launch video? “The most beautiful woman in the world, according to Dove.”

I applaud them for the powerful ad. But I’m perplexed by Dove issuing a statement saying it won’t use AI for images of real beauty and then sharing a branded prompt for doing exactly that. Isn’t it like me saying, “Don’t think of a parrot eating pizza. Don’t think about a parrot eating pizza,” and you can’t help but think about a parrot eating pizza right now?

Brandtech Group says it’s all in on AI

Now, Brandtech Group, a conglomerate ad agency, is going the other way. It’s going all-in on AI and telling everybody.

This week, Ad Age featured a press release — oops, I mean an article (subscription required) — with the details of how Brandtech is leaning into the takeaway from OpenAI’s Sam Altman, who says 95% of marketing work today can be done by AI.

A Brandtech representative talked about how they pitch big brands with two people instead of 20. They boast about how proud they are that its lean 7,000 staffers compete with 100,000-person teams. (To be clear, showing up to a pitch with 20 people has never been a good thing, but I digress.)

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OK, that’s a differentiated approach. They’re all in. Ad Age certainly seemed to like it enough to promote it. Oops, I mean report about it.

False claims of using AI and not using AI

Offshoots of the all-in and never-will approaches also exist.

The term “AI washing” is de rigueur to describe companies claiming to use AI for something that really isn’t AI.  The US Securities and Exchange Commission just fined two companies for using misleading statements about their use of AI in their business model. I know one startup technology organization faced so much pressure from their board and investors to “do something with AI” that they put a simple chatbot on their website — a glorified search engine — while they figured out what they wanted to do.

Lastly and perhaps most interestingly, companies have and will use AI for much of what they create but remain quiet about it or desire to keep it a secret. A recent notable example is the deepfake ad of a woman in a car professing the need for people to use a particular body wipe to get rid of body odor. It was purported to be real, but sharp-eyed viewers suspected the fake and called out the company, which then admitted it. Or was that the brand’s intent all along — the AI-use outrage would bring more attention?

To yell or not to yell about your brand’s AI decision

Should a brand yell from a mountaintop that they use AI to differentiate themselves a la Brandtech? Or should a brand yell they’re never going to use AI to differentiate themselves a la Dove? Or should a brand use it and not yell anything? (I think it’s clear that a brand should not use AI and lie and say it is. That’s the worst of all choices.)

I lean far into not-yelling-from-mountaintop camp.

When I see a CEO proudly exclaim that they laid off 90% of their support workforce because of AI, I’m not surprised a little later when the value of their service is reduced, and the business is failing.

I’m not surprised when I hear “AI made us do it” to rationalize the latest big tech company latest rounds of layoffs. Or when a big consulting firm announces it’s going all-in on using AI to replace its creative and strategic resources.

I see all those things as desperate attempts for short-term attention or a distraction from the real challenge. They may get responses like, “Of course, you had to lay all those people off; AI is so disruptive,” or “Amazing. You’re so out in front of the rest of the pack by leveraging AI to create efficiency, let me cover your story.” Perhaps they get this response, “Your company deserves a bump in stock price because you’re already using this fancy new technology.”

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But what happens if the AI doesn’t deliver as promoted? What happens the next time you need to lay off people? What happens the next time you need to prove your technologically forward-leaning?

Yelling out that you’re all in on a disruptive innovation, especially one the public doesn’t yet trust a lot is (at best) a business sugar high. That short-term burst of attention may or may not foul your long-term brand value.

Interestingly, the same scenarios can manifest when your brand proclaims loudly it is all out of AI, as Dove did. The sugar high may not last and now Dove has itself into a messaging box. One slip could cause distrust among its customers. And what if AI gets good at demonstrating diversity in beauty?

I tried Dove’s instructions and prompted ChatGPT for a picture of “the most beautiful woman in the world according to the Dove Real Beauty ad.”

It gave me this. Then this. And this. And finally, this.

She’s absolutely beautiful, but she doesn’t capture the many facets of diversity Dove has demonstrated in its Real Beauty campaigns. To be clear, Dove doesn’t have any control over generating the image. Maybe the prompt worked well for Dove, but it didn’t for me. Neither Dove nor you can know how the AI tool will behave.

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To use AI or not to use AI?

When brands grab a microphone to answer that question, they work from an existential fear about the disruption’s meaning. They do not exhibit the confidence in their actions to deal with it.

Let’s return to Hamlet’s soliloquy:

Thus conscience doth make cowards of us all;

And thus the native hue of resolution

Is sicklied o’er with the pale cast of thought,

And enterprises of great pith and moment

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With this regard their currents turn awry

And lose the name of action.

In other words, Hamlet says everybody is afraid to take real action because they fear the unknown outcome. You could act to mitigate or solve some challenges, but you don’t because you don’t trust yourself.

If I’m a brand marketer for any business (and I am), I’m going to take action on AI for my business. But until I see how I’m going to generate value with AI, I’m going to be circumspect about yelling or proselytizing how my business’ future is better.

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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How to Use AI For a More Effective Social Media Strategy, According to Ross Simmonds

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How to Use AI For a More Effective Social Media Strategy, According to Ross Simmonds

Welcome to Creator Columns, where we bring expert HubSpot Creator voices to the Blogs that inspire and help you grow better.

It’s the age of AI, and our job as marketers is to keep up.

My team at Foundation Marketing recently conducted an AI Marketing study surveying hundreds of marketers, and more than 84% of all leaders, managers, SEO experts, and specialists confirmed that they used AI in the workplace.

AI in the workplace data graphic, Foundation Labs

If you can overlook the fear-inducing headlines, this technology is making social media marketers more efficient and effective than ever. Translation: AI is good news for social media marketers.

Download Now: The 2024 State of Social Media Trends [Free Report]

In fact, I predict that the marketers not using AI in their workplace will be using it before the end of this year, and that number will move closer and closer to 100%.

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Social media and AI are two of the most revolutionizing technologies of the last few decades. Social media has changed the way we live, and AI is changing the way we work.

So, I’m going to condense and share the data, research, tools, and strategies that the Foundation Marketing Team and I have been working on over the last year to help you better wield the collective power of AI and social media.

Let’s jump into it.

What’s the role of AI in social marketing strategy?

In a recent episode of my podcast, Create Like The Greats, we dove into some fascinating findings about the impact of AI on marketers and social media professionals. Take a listen here:

Let’s dive a bit deeper into the benefits of this technology:

Benefits of AI in Social Media Strategy

AI is to social media what a conductor is to an orchestra — it brings everything together with precision and purpose. The applications of AI in a social media strategy are vast, but the virtuosos are few who can wield its potential to its fullest.

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AI to Conduct Customer Research

Imagine you’re a modern-day Indiana Jones, not dodging boulders or battling snakes, but rather navigating the vast, wild terrain of consumer preferences, trends, and feedback.

This is where AI thrives.

Using social media data, from posts on X to comments and shares, AI can take this information and turn it into insights surrounding your business and industry. Let’s say for example you’re a business that has 2,000 customer reviews on Google, Yelp, or a software review site like Capterra.

Leveraging AI you can now have all 2,000 of these customer reviews analyzed and summarized into an insightful report in a matter of minutes. You simply need to download all of them into a doc and then upload them to your favorite Generative Pre-trained Transformer (GPT) to get the insights and data you need.

But that’s not all.

You can become a Prompt Engineer and write ChatGPT asking it to help you better understand your audience. For example, if you’re trying to come up with a persona for people who enjoy marathons but also love kombucha you could write a prompt like this to ChatGPT:

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ChatGPT prompt example

The response that ChatGPT provided back is quite good:

GPT response example

Below this it went even deeper by including a lot of valuable customer research data:

  • Demographics
  • Psychographics
  • Consumer behaviors
  • Needs and preferences

And best of all…

It also included marketing recommendations.

The power of AI is unbelievable.

Social Media Content Using AI

AI’s helping hand can be unburdening for the creative spirit.

Instead of marketers having to come up with new copy every single month for posts, AI Social Caption generators are making it easier than ever to craft catchy status updates in the matter of seconds.

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Tools like HubSpot make it as easy as clicking a button and telling the AI tool what you’re looking to create a post about:

AI social media caption generator step 1

The best part of these AI tools is that they’re not limited to one channel.

Your AI social media content assistant can help you with LinkedIn content, X content, Facebook content, and even the captions that support your post on Instagram.

It can also help you navigate hashtags:

AI social media hashtags generator example, HubSpot

With AI social media tools that generate content ideas or even write posts, it’s not about robots replacing humans. It’s about making sure that the human creators on your team are focused on what really matters — adding that irreplaceable human touch.

Enhanced Personalization

You know that feeling when a brand gets you, like, really gets you?

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AI makes that possible through targeted content that’s tailored with a level of personalization you’d think was fortune-telling if the data didn’t paint a starker, more rational picture.

What do I mean?

Brands can engage more quickly with AI than ever before. In the early 2000s, a lot of brands spent millions of dollars to create social media listening rooms where they would hire social media managers to find and engage with any conversation happening online.

Thanks to AI, brands now have the ability to do this at scale with much fewer people all while still delivering quality engagement with the recipient.

Analytics and Insights

Tapping into AI to dissect the data gives you a CSI-like precision to figure out what works, what doesn’t, and what makes your audience tick. It’s the difference between guessing and knowing.

The best part about AI is that it can give you almost any expert at your fingertips.

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If you run a report surrounding the results of your social media content strategy directly from a site like LinkedIn, AI can review the top posts you’ve shared and give you clear feedback on what type of content is performing, why you should create more of it, and what days of the week your content is performing best.

This type of insight that would typically take hours to understand.

Now …

Thanks to the power of AI you can upload a spreadsheet filled with rows and columns of data just to be met with a handful of valuable insights a few minutes later.

Improved Customer Service

Want 24/7 support for your customers?

It’s now possible without human touch.

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Chatbots powered by AI are taking the lead on direct messaging experiences for brands on Facebook and other Meta properties to offer round-the-clock assistance.

The fact that AI can be trained on past customer queries and data to inform future queries and problems is a powerful development for social media managers.

Advertising on Social Media with AI

The majority of ad networks have used some variation of AI to manage their bidding system for years. Now, thanks to AI and its ability to be incorporated in more tools, brands are now able to use AI to create better and more interesting ad campaigns than ever before.

Brands can use AI to create images using tools like Midjourney and DALL-E in seconds.

Brands can use AI to create better copy for their social media ads.

Brands can use AI tools to support their bidding strategies.

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The power of AI and social media is continuing to evolve daily and it’s not exclusively found in the organic side of the coin. Paid media on social media is being shaken up due to AI just the same.

How to Implement AI into Your Social Media Strategy

Ready to hit “Go” on your AI-powered social media revolution?

Don’t just start the engine and hope for the best. Remember the importance of building a strategy first. In this video, you can learn some of the most important factors ranging from (but not limited to) SMART goals and leveraging influencers in your day-to-day work:

The following seven steps are crucial to building a social media strategy:

  1. Identify Your AI and Social Media Goals
  2. Validate Your AI-Related Assumptions
  3. Conduct Persona and Audience Research
  4. Select the Right Social Channels
  5. Identify Key Metrics and KPIs
  6. Choose the Right AI Tools
  7. Evaluate and Refine Your Social Media and AI Strategy

Keep reading, roll up your sleeves, and follow this roadmap:

1. Identify Your AI and Social Media Goals

If you’re just dipping your toes into the AI sea, start by defining clear objectives.

Is it to boost engagement? Streamline your content creation? Or simply understand your audience better? It’s important that you spend time understanding what you want to achieve.

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For example, say you’re a content marketing agency like Foundation and you’re trying to increase your presence on LinkedIn. The specificity of this goal will help you understand the initiatives you want to achieve and determine which AI tools could help you make that happen.

Are there AI tools that will help you create content more efficiently? Are there AI tools that will help you optimize LinkedIn Ads? Are there AI tools that can help with content repurposing? All of these things are possible and having a goal clearly identified will help maximize the impact. Learn more in this Foundation Marketing piece on incorporating AI into your content workflow.

Once you have identified your goals, it’s time to get your team on board and assess what tools are available in the market.

Recommended Resources:

2. Validate Your AI-Related Assumptions

Assumptions are dangerous — especially when it comes to implementing new tech.

Don’t assume AI is going to fix all your problems.

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Instead, start with small experiments and track their progress carefully.

3. Conduct Persona and Audience Research

Social media isn’t something that you can just jump into.

You need to understand your audience and ideal customers. AI can help with this, but you’ll need to be familiar with best practices. If you need a primer, this will help:

Once you understand the basics, consider ways in which AI can augment your approach.

4. Select the Right Social Channels

Not every social media channel is the same.

It’s important that you understand what channel is right for you and embrace it.

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The way you use AI for X is going to be different from the way you use AI for LinkedIn. On X, you might use AI to help you develop a long-form thread that is filled with facts and figures. On LinkedIn however, you might use AI to repurpose a blog post and turn it into a carousel PDF. The content that works on X and that AI can facilitate creating is different from the content that you can create and use on LinkedIn.

The audiences are different.

The content formats are different.

So operate and create a plan accordingly.

Recommended Tools and Resources:

5. Identify Key Metrics and KPIs

What metrics are you trying to influence the most?

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Spend time understanding the social media metrics that matter to your business and make sure that they’re prioritized as you think about the ways in which you use AI.

These are a few that matter most:

  • Reach: Post reach signifies the count of unique users who viewed your post. How much of your content truly makes its way to users’ feeds?
  • Clicks: This refers to the number of clicks on your content or account. Monitoring clicks per campaign is crucial for grasping what sparks curiosity or motivates people to make a purchase.
  • Engagement: The total social interactions divided by the number of impressions. This metric reveals how effectively your audience perceives you and their readiness to engage.

Of course, it’s going to depend greatly on your business.

But with this information, you can ensure that your AI social media strategy is rooted in goals.

6. Choose the Right AI Tools

The AI landscape is filled with trash and treasure.

Pick AI tools that are most likely to align with your needs and your level of tech-savviness.

For example, if you’re a blogger creating content about pizza recipes, you can use HubSpot’s AI social caption generator to write the message on your behalf:

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AI social media generator example

The benefit of an AI tool like HubSpot and the caption generator is that what at one point took 30-40 minutes to come up with — you can now have it at your fingertips in seconds. The HubSpot AI caption generator is trained on tons of data around social media content and makes it easy for you to get inspiration or final drafts on what can be used to create great content.

Consider your budget, the learning curve, and what kind of support the tool offers.

7. Evaluate and Refine Your Social Media and AI Strategy

AI isn’t a magic wand; it’s a set of complex tools and technology.

You need to be willing to pivot as things come to fruition.

If you notice that a certain activity is falling flat, consider how AI can support that process.

Did you notice that your engagement isn’t where you want it to be? Consider using an AI tool to assist with crafting more engaging social media posts.

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Make AI Work for You — Now and in the Future

AI has the power to revolutionize your social media strategy in ways you may have never thought possible. With its ability to conduct customer research, create personalized content, and so much more, thinking about the future of social media is fascinating.

We’re going through one of the most interesting times in history.

Stay equipped to ride the way of AI and ensure that you’re embracing the best practices outlined in this piece to get the most out of the technology.

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MARKETING

Advertising in local markets: A playbook for success

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Advertising in local markets: A playbook for success

Many brands, such as those in the home services industry or a local grocery chain, market to specific locations, cities or regions. There are also national brands that want to expand in specific local markets. 

Regardless of the company or purpose, advertising on a local scale has different tactics than on a national scale. Brands need to connect their messaging directly with the specific communities they serve and media to their target demo. Here’s a playbook to help your company succeed when marketing on a local scale.  

1. Understand local vs. national campaigns

Local advertising differs from national campaigns in several ways: 

  • Audience specificity: By zooming in on precise geographic areas, brands can tailor messaging to align with local communities’ customs, preferences and nuances. This precision targeting ensures that your message resonates with the right target audience.
  • Budget friendliness: Local advertising is often more accessible for small businesses. Local campaign costs are lower, enabling brands to invest strategically within targeted locales. This budget-friendly nature does not diminish the need for strategic planning; instead, it emphasizes allocating resources wisely to maximize returns. As a result, testing budgets can be allocated across multiple markets to maximize learnings for further market expansion.
  • Channel selection: Selecting the correct channels is vital for effective local advertising. Local newspapers, radio stations, digital platforms and community events each offer advantages. The key lies in understanding where your target audience spends time and focusing efforts to ensure optimal engagement.
  • Flexibility and agility: Local campaigns can be adjusted more swiftly in response to market feedback or changes, allowing brands to stay relevant and responsive. 

Maintaining brand consistency across local touchpoints reinforces brand identity and builds a strong, recognizable brand across markets. 

2. Leverage customized audience segmentation 

Customized audience segmentation is the process of dividing a market into distinct groups based on specific demographic criteria. This marketing segmentation supports the development of targeted messaging and media plans for local markets. 

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For example, a coffee chain might cater to two distinct segments: young professionals and retirees. After identifying these segments, the chain can craft messages, offers and media strategies relating to each group’s preferences and lifestyle.

To reach young professionals in downtown areas, the chain might focus on convenience, quality coffee and a vibrant atmosphere that is conducive to work and socializing. Targeted advertising on Facebook, Instagram or Connected TV, along with digital signage near office complexes, could capture the attention of this demographic, emphasizing quick service and premium blends.

Conversely, for retirees in residential areas, the chain could highlight a cozy ambiance, friendly service and promotions such as senior discounts. Advertisements in local print publications, community newsletters, radio stations and events like senior coffee mornings would foster a sense of community and belonging.

Dig deeper: Niche advertising: 7 actionable tactics for targeted marketing

3. Adapt to local market dynamics

Various factors influence local market dynamics. Brands that navigate changes effectively maintain a strong audience connection and stay ahead in the market. Here’s how consumer sentiment and behavior may evolve within a local market and the corresponding adjustments brands can make. 

  • Cultural shifts, such as changes in demographics or societal norms, can alter consumer preferences within a local community. For example, a neighborhood experiencing gentrification may see demand rise for specific products or services.
    • Respond by updating your messaging to reflect the evolving cultural landscape, ensuring it resonates with the new demographic profile.
  • Economic conditions are crucial. For example, during downturns, consumers often prioritize value and practicality.
    • Highlight affordable options or emphasize the practical benefits of your offerings to ensure messaging aligns with consumers’ financial priorities. The impact is unique to each market and the marketing message must also be dynamic.
  • Seasonal trends impact consumer behavior.
    • Align your promotions and creative content with changing seasons or local events to make your offerings timely and relevant.
  • New competitors. The competitive landscape demands vigilance because new entrants or innovative competitor campaigns can shift consumer preferences.
    • Differentiate by focusing on your unique selling propositions, such as quality, customer service or community involvement, to retain consumer interest and loyalty.

4. Apply data and predictive analytics 

Data and predictive analytics are indispensable tools for successfully reaching local target markets. These technologies provide consumer behavior insights, enabling you to anticipate market trends and adjust strategies proactively. 

  • Price optimization: By analyzing consumer demand, competitor pricing and market conditions, data analytics enables you to set prices that attract customers while ensuring profitability.
  • Competitor analysis: Through analysis, brands can understand their positioning within the local market landscape and identify opportunities and threats. Predictive analytics offer foresight into competitors’ potential moves, allowing you to strategize effectively to maintain a competitive edge.
  • Consumer behavior: Forecasting consumer behavior allows your brand to tailor offerings and marketing messages to meet evolving consumer needs and enhance engagement.
  • Marketing effectiveness: Analytics track the success of advertising campaigns, providing insights into which strategies drive conversions and sales. This feedback loop enables continuous optimization of marketing efforts for maximum impact.
  • Inventory management: In supply chain management, data analytics predict demand fluctuations, ensuring inventory levels align with market needs. This efficiency prevents stockouts or excess inventory, optimizing operational costs and meeting consumer expectations.

Dig deeper: Why you should add predictive modeling to your marketing mix

5. Counter external market influences

Consider a clothing retailer preparing for a spring collection launch. By analyzing historical weather data and using predictive analytics, the brand forecasts an unseasonably cool start to spring. Anticipating this, the retailer adjusts its campaign to highlight transitional pieces suitable for cooler weather, ensuring relevance despite an unexpected chill.

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Simultaneously, predictive models signal an upcoming spike in local media advertising rates due to increased market demand. Retailers respond by reallocating a portion of advertising budgets to digital channels, which offer more flexibility and lower costs than traditional media. This shift enables brands to maintain visibility and engagement without exceeding budget, mitigating the impact of external forces on advertising.

6. Build consumer confidence with messaging

Localized messaging and tailored customer service enhance consumer confidence by demonstrating your brand’s understanding of the community. For instance, a grocery store that curates cooking classes featuring local cuisine or sponsors community events shows commitment to local culture and consumer interests. 

Similarly, a bookstore highlighting local authors or topics relevant to the community resonates with local customers. Additionally, providing service that addresses local needs — such as bilingual service and local event support — reinforces the brand’s values and response to the community. 

Through these localized approaches, brands can build trust and loyalty, bridging the gap between corporate presence and local relevance.

7. Dominate with local advertising 

To dominate local markets, brands must:

  • Harness hyper-targeted segmentation and geo-targeted advertising to reach and engage precise audiences.
  • Create localized content that reflects community values, engage in community events, optimize campaigns for mobile and track results.
  • Fine-tune strategies, outperform competitors and foster lasting relationships with customers.

These strategies will enable your message to resonate with local consumers, differentiate you in competitive markets and ensure you become a major player in your specific area. 



Dig deeper: The 5 critical elements for local marketing success

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Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.

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