How to Use Artificial Intelligence to Boost Profit from Your B2B Blog

how to use artificial intelligence

Artificial intelligence shapes almost all your digital experiences. Despite our daily exposure to AI, many B2Bs still aren’t sure how to use it effectively just yet.

Apps like Netflix offer an endless stream of personalized content.

Facebook is specially designed to keep you scrolling with uniquely crafted content.

Amazon offers personalized product suggestions to keep you buying.

Research shows 40% of B2Bs using AI believe it’s an important investment to achieve better sales and marketing outcomes. A third go as far as to say AI is revolutionizing B2B marketing entirely.

The future doesn’t look good for those who fail to adopt successful AI strategies.

Furthermore, evidence says 80% of businesses will abandon their data-driven personalization strategies due to poor ROI by 2025. AI is the missing link that connects data and content to create effective personalized experiences.

Here’s how to use artificial intelligence to improve your blog strategy.

how to use artificial intelligence

How to Use Artificial Intelligence to Boost the Effectiveness of Your B2B Blog

Artificial intelligence creates personalized experiences better than a human marketer ever could. Instead of spending hours sifting through massive datasets and drawing conclusions for a tiny return, AI can complete the tasks more effectively in a fraction of the time.

1. Organize Your Content More Efficiently for Visitors

Traditional blogs aren’t user-friendly. They usually contain broad categories for topics and some tags for organization.

Beyond recommended content you add manually, there’s no personalization – and especially no hyper-personalization.

Instead, AI can help you create unique experiences for everyone with adaptive content hubs. An adaptive content hub uses machine learning to suggest relevant posts based on each user’s behavior AND the behavior of past similar users.

2. Offer Personalized Content Recommendations

When you implement AI on your website, you don’t have to go through the trouble of segmenting your leads into different boxes and following up with chosen content recommendations.

AI uses every visitor’s browsing behavior, the behavior of similar users, and intent data to provide personalized content recommendations for everyone.

Once a lead provides their email address, you can follow up with even more personalized nurturing content based on the piece of content that pushed them over the edge.

AI uses the same algorithms as Amazon and Netflix, such as collaborative filtering and content similarity models, to learn about visitors and improve experiences.

Hushly

3. Guide Leads Down the Sales Funnel

Artificial intelligence doesn’t just improve the visitor experience, it also helps you nurture leads while you sleep.

The algorithms are specially designed to select the perfect piece of content for every stage of the sales funnel. The algorithms gently guide visitors toward a purchase while they browse your site.

And when they return to your site, the algorithms remember them and pick up right where they left off!

In other words, you can start nurturing visitors right away before you ever collect their email address.

4. Allow Leads to Self-Nurture and Research at Their Own Pace

Part of nurturing is delivering the right piece of content to leads at the perfect time.

Considering that buyers complete up to 90% of the sales process without contacting anyone at your company, it’s important to give them the tools they need to research.

Understanding how to use artificial intelligence on your website can simplify the process.

Instead of following up through email or retargeting ads on social media (which are both effective in their own rights), you can use your website to help nurture leads with content bingeing features.

Self-nurturing landing pages follow a similar strategy as Netflix: Offer personalized content recommendations to keep visitors on the website.

5. Create an Effective Account-Based Marketing Strategy

Account-based marketing can deliver incredible returns IF you can get the right strategy in order. If not, ABM turns into a money pit.

Artificial intelligence has made it easier than ever for B2Bs to create effective account-based marketing strategies for the simple reason that AI does the challenging work. Artificial intelligence puts the right piece of content in front of visitors at the right time.

You can also use AI to identify company patterns and figure out which accounts to target for creating content.

6. Ditch Gated Content to Create a Better Experience for Mobile Users

Lead forms are outdated. Think with Google estimates that 70% of B2B searches happen on mobile devices. The last thing anyone on a smartphone wants to do is fill out an intrusive form.

You invested money into researching and creating awesome content. People come to your website for great content. Give it to them.

You don’t have to worry about collecting lead data because artificial intelligence will pick up right where it left off in the nurturing department when they return to the site. You can also use the same data to target anonymous visitors off your site on platforms like LinkedIn with nothing more than a URL from your blog.

7. Catch Visitors Before They Bounce with Personalized Exit-Intent Popups

How many times today have you tried to navigate away from a website only to have it throw a lead magnet form in your face?

Probably quite a few. Unfortunately, the last thing anyone wants to do as they try to leave a site is hand over their personal information. Instead, use artificial intelligence to create a popup with personalized content recommendations.

Not only will people stay on your site longer, but the algorithms can nurture them towards a purchase as well.

Artificial Intelligence is the Future of B2B Marketing

Now that you understand how to use artificial intelligence in B2B marketing, it’s time to implement an AI engine on your site.

Hushly AI uses innovative machine learning to create a personalized experience for everyone, no matter whether they’re a known lead you’ve collected or an anonymous web visitor.

You’re already collecting the data. Why not put it to work with the power of AI?

how to use artificial intelligence

6 Strategies to Use Artificial Intelligence in Business Marketing

the use of artificial intelligence in business

Artificial intelligence is taking over every industry.

When people think of AI, they tend to imagine robotic devices completing human tasks like bagging groceries or grilling burgers. The reality is, however, the use of artificial intelligence in business goes much deeper than that.

At least 18% of B2Bs already use AI in their marketing strategies and that figure rises every day. Plus, AI is effective. 84% of businesses using AI expect to see a return on their investment within a year.

Despite its growing prevalence in the business world, some marketers are still reluctant to adopt AI technology into their strategies. Here are a few tools and ideas to get you started.

the use of artificial intelligence in business

6 Benefits of Using Artificial Intelligence in Business

Artificial intelligence makes marketing work easier – A LOT easier.

Long gone are the days of sifting through massive data sets, piecing together segments, creating personalized content, and struggling to deliver it at the perfect time.

AI removes marketing’s most tedious work so you have more time to work on creating incredible content, connecting with leads, and building your social strategies.

1. Creating a Personalized Experience for Everyone

B2B buyers demand personalization. 85% of buyers will write off a vendor that doesn’t personalize the very first touchpoint. That’s a lot of pressure but the use of artificial intelligence in business marketing can create a personalized experience for everyone based on behavioral data.

2. Scoring Leads

Just think of how much time your team spends scoring leads each week. Artificial intelligence can sort through massive datasets faster and better than any human can. Not only does it make lead scoring easier, it delivers better results too.

3. Keeping Websites Secure

Cybersecurity is a major concern for B2Bs. According to the FBI, 50% of cybercrime targets B2B payment systems. Artificial intelligence can protect your processing systems and protect your databases from hacks.

4. Helping Leads Self-Nurture

Buyers complete up to 90% of the buying process alone without ever reaching out to anyone at your sales team. It’s important for all businesses to build websites that allow leads to conduct effective research with minimal time and effort.

AI and machine learning cater to your leads’ demand for instant gratification so they can research at their own pace without forms getting in the way.

5. Preventing Customer Churn

80% of B2B buyers will switch suppliers within the first two years citing poor customer experiences. You can identify potential churn and stop it in its tracks with powerful AI. Plus, using AI-driven website experiences can help customers feel appreciated and valued.

6. Verifying Lead Information

Did you know most B2B marketers are basing their strategies on data up to 40% incorrect? Not good.

It’s no surprise that an estimated 80% of businesses will abandon their data-driven personalization strategies by 2025.

Artificial intelligence removes the problem of bad data at its source by verifying lead data upon entry through publicly available information sources.

How Do Companies Use Artificial Intelligence?

Now that we’ve gone over some of the benefits, let’s look at how AI is changing business marketing for the better. Here are a few practical applications.

1. Human Lead Verification

Another piece of lead data expires every day. Every year

  • 34% of your leads change job functions or titles
  • 37% change their email address
  • 30% change jobs
  • 34% of companies change names

With an AI engine on your site, you don’t have to rely on collecting static lead information. Instead, AI cross-references every lead’s business email with publicly available information on sources like LinkedIn so it’s always accurate.

This is good for your leads too because it means they don’t have to spend time filling out forms when you’re only collecting an email address.

2. Personalized Exit-Intent Popups

Let’s be honest. No one wants to fill out a form as they’re trying to leave your website.

AI can help you prevent bounces and exits with personalized content recommendations.

Instead of confronting your visitors with an intrusive form asking for data while they try to tab away, they’ll receive a popup filled with relevant and useful content.

3. Chatbots

Chatbots have come a long way in the past few years. You don’t have to feel weird about adding chatbots to your site either because visitors have come to expect them.

People spend so much time online each day and they still crave conversation. AI-driven chatbots use machine learning to simulate real conversations and fill the gap where workers can’t.

4. Adaptive Content Hubs

Adaptive content hubs remove the old blog interface in favor of a technology-driven upgrade. Instead of forcing your visitors to scroll through categories and backward through old posts, AI offers personalized recommendations for everyone.

Using the same collaborative filtering and other algorithms like Amazon, machine learning studies your visitors and improves the longer you use it!

Hushly

5. Self-Nurturing Landing Pages

Remember your leads complete up to 90% of the sales process alone without ever communicating with someone at your company. Self-nurturing landing pages are vital for giving them the tools they need.

A self-nurturing landing page uses content bingeing features and AI-driven algorithms – just like Netflix – to keep users hooked.

6. Effective Account-Based Marketing Strategies

Account-based marketing has picked up plenty of steam over the past few years and we have technology to thank for that.

AI makes it easier than ever to create relevant content for specific accounts and target them at the perfect time. You no longer need a massive marketing budget to pull off an effective ABM strategy because you have the power of efficient AI.

Embrace the Use of Artificial Intelligence in Business Marketing and Watch Leads Skyrocket

Hushly AI creates a personalized experience for everyone who visits your website – whether known or anonymous. You can spend less time organizing content on your website and nurturing leads because AI takes control of everything. Plus, it’s much more effective than humans!

the use of artificial intelligence in business

How Companies are Using Artificial Intelligence (And You Can Too)

companies using artificial intelligence

Leading companies around the world are using AI to reach their audience and provide personalized experiences.

A few years ago, businesses assumed AI was only accessible to the big guys with massive budgets to throw around on new tools and software. Currently, an estimated 18% of B2Bs are using artificial intelligence, and you can expect that figure to skyrocket over the next few years.

AI works because it helps businesses provide relevant content. That’s why 84% of those using AI expect to see value within a year.

The truth is, AI is easy to add to your B2B website. You don’t need to have in-depth coding knowledge or a dedicated team to implement it. Just plug it in and you’re ready to go.

But what does AI look like in practice? Here are a few companies using artificial intelligence and how you can use their strategies as inspiration.

companies using artificial intelligence

4 Leading Companies Using Artificial Intelligence and How to Take Advantage of It

From personalized content recommendations to preventing abandonment, you can follow some of the top companies using artificial intelligence.

1. Top Companies Using Artificial Intelligence: Amazon

Amazon is one of the leaders in AI but no one talks about it anymore because we’ve become so used to it. That’s the thing about personalized content recommendations: Everyone expects them, including your leads.

Research shows that 75% of B2B buyers now expect brands to anticipate their needs and provide relevant content.

Amazon has nailed down personalized recommendations thanks to machine learning and certain algorithms. Here are a few of them:

  • Content similarity model: An algorithm monitors which products you viewed and provides personalized recommendations.
  • Collaborative filtering model: An algorithm recommends products based on what users with similar buying behavior purchased. These are the “customers ultimately bought” or “customers also bought” suggestions you see.

Hushly

These algorithms work. Did you know those personalized suggestions account for about 35% of all Amazon purchases?

Takeaway:

You can easily bring personalized content suggestions to your B2B landing pages and blog because Hushly offers Adaptive Content Hubs to upgrade your content marketing.

Instead of forcing your visitors to navigate backward through your blogs, an Adaptive Content Hub supplies personalized content recommendations using collaborative filtering, content similarity, and several other algorithms.

Just like Amazon, the Adaptive Content Hub uses every visitor’s browsing behavior AND the behavior of similar visitors to create a personalized experience for everyone.

2. Top Companies Using Artificial Intelligence: Netflix

Like Amazon, Netflix also provides personalized content recommendations using several algorithms like content similarity models and collaborative filtering. In fact, 75% of all Netflix views come from these personalized recommendations.

Netflix also highlights other algorithm models such as:

  • Trending assets: Trending recommendations based on what’s hot right now.
  • Important assets: Netflix deems its own original content important and suggests it regularly.

There’s another reason the streaming giant is so successful: content bingeing. Netflix doesn’t let you go after you watch one movie or TV show. Oh no, it offers a constant stream of content that autoplays when one show finishes – whether you want it to or not!

Takeaway:

Traditional landing pages are outdated, and Netflix shows us that content bingeing works. Instead of leaving your visitors at a dead-end, smash those 1% conversion rates with self-nurturing landing pages.

A self-nurturing landing page offers your visitors an endless stream of personalized content recommendations thanks to machine learning and AI algorithms.

3. Top Companies Using Artificial Intelligence: Microsoft

Is there any platform with more natural conversations than Reddit? Almost everyone on Reddit remains anonymous so conversations are deep and often flow on and on in detailed threads.

Well, Microsoft is partnering with Reddit to improve its natural language processing for chatbots. As you can imagine, there are still a few kinks to work out – especially with respect to NSFW content – but the system seems to work well!

Takeaway:

You can bring the same data collaboration to your website with the power of AI. Artificial intelligence is perfect for verifying leads.

Research shows 62% of businesses are basing their business decisions off data up to 40% incorrect. Yikes. Unfortunately, that’s going to happen unless you can use AI to verify your lead data.

Instead of collecting a bunch of information on leads that expires within days (like company names, job roles, etc.), all you need is a business email address and a country. That’s it! The AI system will verify lead data with public information on LinkedIn so it’s always correct and current.

4. Top Companies Using AI: Tencent

Tencent is one of China’s leaders in artificial intelligence. The company’s vision is to “make AI everywhere” and they’re taking that mission seriously with content, advertising, cloud storage, and even online gaming.

Tencent alone hosts 55% of China’s entire mobile internet usage. That’s huge considering China is the world’s largest market.

Companies using artificial intelligence in gaming, like Tencent, have mastered the art of preventing abandonment by recommending similar content to keep users hooked.

Takeaway:

You can add AI to your abandonment strategy with Hushly. Instead of bombarding your precious visitors with an annoying form, you can deliver personalized content recommendations with exit-intent popups.

People are much more likely to stay on your site when you give them more relevant and valuable content instead of asking them to complete a task by filling out a form. It’s a win-win for everyone: you AND your visitors.

Here’s what a personalized exit-intent popup looks like in action:

Hushly

Become One of the Leaders in AI

Hushly makes AI accessible to everyone. With Hushly, you don’t need extensive coding knowledge to provide your visitors with personalized experiences. Just add the platform to your website and watch your lead conversions skyrocket by 51% thanks to hyper-personalized content recommendations.

The Hushly AI engine uses machine learning to study every visitor and deliver a unique experience – whether they’re a known lead or an anonymous visitor.

companies using artificial intelligence

5 Tools You Need to Create a Personalized Customer Experience

personalized customer experience

Personalization is the big marketing buzzword of the year again it seems.

For the past few years, consumer brands have upped their marketing games with personalized content and customer journeys.

88% of B2Bs say buyers expect more personalized experiences than they did just five years ago.

Despite this, B2Bs have been reluctant to accept personalization and AI-driven technology but they’re slowly catching on.

personalized customer experience

Why Use Customized Marketing for Each Visitor?

A personalized customer experience in B2B allows you to create a unique experience for every visitor – whether known or anonymous.

Using AI machine learning, algorithms monitor the behavior of everyone who visits your website.

  • What posts are they reading?
  • How long did they spend on each post?
  • What did they click to read next?
  • What have similar visitors read?

85% of buyers say they’ll consider dismissing a vendor that fails to personalize the very first interaction.

The entire buyer journey has gone digital too, so website personalization is vital at every touchpoint. Buyers complete up to 90% of the buying process on their own without ever contacting a sales team.

Not only does a personalized customer experience satisfy buyer expectations for personalized content but it also helps guide visitors down the buying process without even collecting their contact details.

Through machine learning, algorithms gently nudge visitors towards conversion by recommending the perfect piece of content and the ideal time.

There’s no need to force visitors to fill out an annoying clunky form. No need to analyze visitor data looking for insights and patterns.

The algorithm handles everything in real time.

5 Tools to Create a Personalized Customer Experience for Everyone

AI and personalization aren’t as complicated as they sound. Yes, the technology behind a personalized customer experience is complicated. On the end user’s side, however, it’s remarkably simple and easy to understand.

Here are a few tools and tips you can use almost immediately to create a customized marketing experience for every visitor – whether a collected lead or an anonymous web browser.

1. Use Human Lead Verification to Start with Clean Data

Effective personalized communication and content starts with high-quality data. For data to be high-quality, it needs to be current and correct.

Unfortunately, most businesses are using data up to 40% incorrect to make important marketing decisions. It’s no surprise that 40% of business goals fail with bad intel as the culprit.

Bad data is costly too. It takes $10 to scrub a bad piece of information from your system later and $100 if you let it stay there and throw off your analysis.

Research shows 80% of businesses will abandon their data-driven personalization strategies due to poor ROI for just this reason.

Here’s the good news: AI-driven lead verification systems can remove the problem at its source.

Instead of manually verifying lead data as it’s entered and on an ongoing basis, algorithms cross-reference a business address with public information on LinkedIn.

Not only does this remove forms (all you need is a business email) to make the process easier for leads, but it also helps you build comprehensive profiles on different lead segments or accounts.

2. Create Data-Driven Content for Different Segments

Once you get your intel in order, you need to use it for content creation.

According to LinkedIn:

  • 49% of buyers consume video during the buying process
  • 64% listen to podcasts to learn about companies
  • 76% like consuming infographics

Different people prefer to ingest information in unique ways. Part of customized marketing involves figuring out what each of your lead segments, audience, or accounts prefer and creating the right types of content.

You could also look for where visitors exit your site. Is there a missing answer to a question you could solve? Could you dig deeper to explain a concept?

3. Add Self-Nurturing Landing Pages for Content Bingeing

Traditional landing pages are outdated. Each landing page contains a single call-to-action. If a visitor doesn’t convert, they disappear into the void.

It’s no wonder B2B conversion rates hover around 1% on average.

Sure, the buying process is much longer in B2B, but marketers should do everything possible to help visitors nurture themselves.

Buyers want to be in control of the process, and they spend up to three hours researching from their phone every day. Your website is your most valuable asset so why not treat it that way?

Self-nurturing landing pages allow visitors to binge content in an endless stream of recommendations based on their behavior and intent. Yep, just like Netflix except your algorithm guides visitors towards conversion.

4. Use Adaptive Content Hubs to Create a Personalized Customer Experience

Like landing pages, traditional blog interfaces are also outdated.

Visitors have to sort through the most recent posts in broad categories to find something that speaks to them.

If they don’t see something on the first page, they’ll go somewhere else.

What happens if you have an amazing piece of content they’d love but it’s buried six pages away? They’d never find it!

An adaptive content hub solves this problem at the source. Yes, your content is organized into broad categories. However, the algorithm watches the visitor’s behavior, compares it to the behavior of previous visitors, and offers personalized content recommendations with high accuracy.

5. Prevent Abandonment with Exit-Intent Popups

Exit-intent popups are everywhere these days.

Sadly, most B2Bs use them in the worst way possible: confronting visitors with a lead form.

Google estimates 70% of all B2B searches happen on mobile devices now. It’s important to create an entirely mobile-friendly experience from start to finish and lead forms simply don’t fit the bill.

Instead, offer your leads MORE personalized content recommendations as they try to leave. You’ll be much more likely to win their hearts when you aren’t asking them to give you their personal information.

Source: Hushly

Use AI for Personalized Communication and Watch Leads Grow

Creating a personalized customer experience is easier than you expect! Hushly can help you capitalize on the AI-driven personalization tools so many leading B2B companies already use.

You no longer have to sort through massive datasets looking for patterns and following up with content recommendations. The algorithm handles everything in real time.

personalized customer experience

6 Tips to Keep Customers Happy with Database Marketing

database marketing

Database marketing isn’t a new concept.

However, emerging technology and digital communication has made it easier than ever for businesses to collect information on their leads and customers.

With better information, you can create personalized experiences and the unique content your leads expect.

Learning how to use technology to your advantage is vital: 88% of businesses say buyers expect more relevant and personalized content compared to five years ago.

database marketing

What is Database Marketing?

Database marketing has been around forever.

Before the internet, companies could collect information on customers and leads through store scanners, surveys, and other means.

Today, however, the internet makes it easy to collect contact information and company firmographics on your leads. Not only that, but you can also collect behavioral data and allow AI to use it in creating a personalized experience.

In the past, using a database might have involved using scanner data to send personalized coupons to a customer’s home. Today, we can use our databases to learn about our audience’s needs and even predict future behavior!

6 Tips and Ideas to Use Database Marketing to Keep Customers and Leads Satisfied

What does database marketing look like in practice in 2020? Here are a few tips, ideas, and tools you can use.

1. Use AI to Verify Lead Data

Effective marketing starts with exact data. Unfortunately, research suggests that 80% of B2Bs will abandon their personalization strategies by 2025 due to low ROI from poor data.

Bad data is truly the silent killer behind an estimated 40% of business objectives.

25% of business databases contain critical errors. Meanwhile, 62% of businesses are relying on data up to 40% wrong to base their marketing decisions.

Artificial intelligence can help make sure your database is clean and healthy.

When someone converts into a lead by providing an email address, an algorithm checks out their public information on sources like LinkedIn to put a list together of:

  • Which company they work for
  • Their job title
  • Their role and duties
  • Industry
  • Company size
  • First and last name
enrichment process

Source: Hushly

Not only does this help you build comprehensive profiles on your leads, but it also means your leads ONLY have to provide an email address. That’s right: No more annoying forms!

2. Create Highly Relevant Content

Database marketing is especially effective for creating highly relevant and valuable content for your audience.

High-quality content is especially important these days because 63% of senior execs say the content they consume daily is far too generic. B2Bs need to do everything they can to stand out and offer nuance to their content.

Using behavioral data, you can segment your audience based on factors like

  • Which companies and industries they work in
  • Job role and power in the decision-making process
  • Stage of the buying cycle
  • Common problems and needs
  • Recurring interests and topics

You can also segment your audience based on which type of content they like such as:

  • Blogs
  • eBooks
  • Podcasts
  • Video
  • Case studies and testimonials

3. Send Automated Email Marketing Database Campaigns

Most marketers are already familiar with email as database marketing. However, innovative technology can help you personalize and automate your email marketing.

You can set up detailed campaigns ahead of time and send them out to new leads and current customers.

Start with a personalized welcome campaign for leads in one industry or even specific companies. A few days later, you could send an onboarding campaign explaining how your business can solve their unique problems or meet their needs. Next week, your lead could receive case studies referencing companies similar to your lead’s.

For current customers in your database, you could send personalized emails with relevant coupons, industry blogs, and events based on data in your system.

Of course, you can create these emails far ahead of time and trigger them to go out at specific times. That’s the beauty of AI!

4. Create Personalized Retargeting Ads on Social Media

You can stretch your dollar far on social media when you use data to drive your campaigns.

For starters, you can use your customer database to create personalized campaigns and ask LinkedIn or Facebook to target the specific email addresses or names. Campaigns like these are useful for maintaining relationships with your current customers to prevent churn.

You can follow the same strategy with your leads and build on the conversation. You can even target unknown visitors before they give you their email address. Instead, plug a URL from a personalized blog into the LinkedIn ad creator to target users who visited that specific URL.

5. Try an Account-Based Marketing Strategy

Database marketing is perfect for transitioning to an account-based marketing strategy.

When you ONLY collect business email addresses and rely on AI to fill in the company details, you can rest assured knowing that your data is more accurate. Accurate intel is vital to ABM success.

Once you’ve collected a few leads from the same company, you can then create personalized content like blogs, videos, eBooks, and email campaigns.

6. Send a Thank You Message

Of course, nothing beats some good old-fashioned courtesy.

Research shows 80% of buyers will switch vendors in 24 months. It’s safe to say many B2Bs spend too much time generating leads and NOT enough time preventing customer churn.

Email will do simply fine. But why not send some direct mail? A thank you message and a small Starbucks gift card or goodie basket can go a long way. Include a QR code or link to a survey where your customer can tell you how they feel about your service.

Boost Your Content Strategy with AI

Adding AI-driven software to your B2B site can help you skyrocket your database marketing strategy. Instead of relying on outdated data to drive your marketing decisions, AI uses machine learning and works in real time to provide personalized content to every visitor.

Whether a web visitor is a collected lead, current customer, or anonymous browser, you can STILL give them a personalized self-nurturing experience!

database marketing

How to Create a Personalized ABM Strategy

ABM strategy

Account-based marketing is here to stay.

With so much technology at your fingertips, it’s almost foolish for B2Bs NOT to have a dedicated ABM strategy.

ABM works when done right because it’s highly personalized and relevant. Your B2Bs expect personalization with 85% saying they’ll dismiss a vendor that doesn’t personalize the very first interaction.

Businesses say their ABM campaigns are worth the money and effort too. 97% of those with ABM say it delivers a higher return than traditional marketing techniques.

It makes sense: ABM is naturally relevant.

However, ABM also involves higher risks along with nice rewards. You have to put in the work and research for that ROI.

Without proper research, strategy, and delivery, your ABM campaign will fall flat. Needless to say, you’ll have to eat a ton of money and time as a loss.

ABM strategy

7 Steps to Creating an Effective ABM Strategy

By following a few key steps and taking advantage of the right martech tools, you can win at your ABM strategy. Here’s how.

1. Identify Your Accounts to Target

Before anything else, you’ll have to figure out which accounts you’ll target so you can strategize how to win them over.

The key here is research and insight.

Start by looking at accounts you’ve already won. You could develop an ABM strategy for them to prevent churn and upsell new products or services. Plus, targeting your key customers will also help you hone your ABM tactics before you develop a new ABM campaign to target fresh leads.

When you’re ready to expand, do some market research and look for gaps in companies you could fill. Do you offer anything your competitors can’t match? Which companies would be most likely to switch? Data is key here.

2. Create Highly Relevant Content

An effective ABM strategy starts with highly relevant and valuable content. Focus on problems your target accounts face and how to solve them.

Strive for nuance here as much as possible.

63% of senior execs say the content they consume during the buying process is too generic and that simply won’t fly in an ABM campaign. Authority is an absolute must.

All the AI and martech tools in the world can’t help you if your content isn’t authoritative, informative, relevant, and hard-hitting.

It’s also important to create content in formats your accounts want to consume. Aim for a healthy mix of video explainers, case studies, eBooks, and audio formats like podcasts.

3. Use an Adaptive Hub to Distribute Content on Your Site

Traditional blog interfaces are outdated. No one has time to sift through broad categories and your recent posts to find the information they need or want.

When you’re publishing so much high-quality content, the last thing you want to do is force leads and prospects to dig for it. You want it accessible, right?

An Adaptive Content Hub uses the power of AI to provide a personalized experience to every visitor. Instead of forcing them to search your site, AI gives them personalized content recommendations based on their behavior and the behavior of previous similar visitors.

4. Implement Self-Nurturing Landing Pages

Self-nurturing landing pages bring content bingeing to your B2B website.

B2Bs complete up to 90% of the buyer’s journey alone without contacting anyone from your company. Meanwhile, average B2B conversion rates hover around 1%.

Instead of presenting prospects and leads with dead-end landing pages, you can use AI to offer a constant stream of personalized content recommendations – just like Netflix!

Visitors will stay on your site longer and bounce rates go down. Plus, the algorithms are designed to gently nurture leads with content that guides them towards converting.

5. Set up Personalized Email Campaigns

Email marketing is one of the most effective tools for nurturing leads in your ABM strategy. Campaigns work because email is easy to automate, segment, and personalize with minimal effort.

Get your campaigns ready to go before a lead ever signs up for your list and create an entire series to guide leads towards conversion. You’ll need:

  • Welcome
  • Onboarding
  • Case studies or tutorials
  • Events and webinars
  • Surveys and polls

Make sure each campaign is highly personalized for the accounts you’re targeting. You can even create unique email series for distinct roles at each company – from C-suite employees down to end users.

This is where AI verification comes in handy.

Instead of relying on retroactive and outdated data, AI-driven lead verification systems check every email address and build profiles based on publicly available information on LinkedIn.

enrichment process

Source: Hushly

6. Send out Social Media Retargeting Ads

LinkedIn is also an effective retargeting tool for your ABM strategy.

Once you have account-specific content on your website, you can paste the URL of a relevant post into LinkedIn’s campaign creator and ask the platform to target people who visited that specific page.

Use this as an opportunity to keep the conversation going.

Whatever problem you addressed in the blog post, follow up with recent stats or insights in your retargeting campaigns.

7. Prepare a Social Selling Strategy

Some industries attribute over 50% of their revenue to social selling tactics!

Reviews are critical in the consumer sector because people trust other consumers more than the brands advertising to them. You can take advantage of this same concept in B2B with social selling.

Find key social accounts and blogs your target companies trust and consume. Build conversations here and ask questions. You can gain some key insights this way.

Add AI to Your Site and Skyrocket Your ABM Strategy

It’s impossible to succeed in your ABM strategy without the right pieces of technology. Artificial intelligence makes it easy to personalize every interaction on your website. Your visitors get a unique experience whether you’ve collected their lead details or not thanks to the power of machine learning.

Plus, it’s easy to implement. Hushly AI just takes a few hours to set up and you’re good to go. You’ll never pay for fake leads or using the platform – just genuine leads.

ABM strategy

Do You Really Need an Online Recommendation Engine in B2B?

online recommendation engine

Despite its pervasiveness in the consumer sector, many B2Bs still seem reluctant to admit that B2B buyers expect a personalized experience.

Even B2Bs who do offer some personalization fall short with delivering results.

Research estimates that 80% of B2Bs will abandon their personalization strategy by 2025 due to poor ROI. Yikes.

The problem lies in how businesses collect and use their data. What they may not realize is that an online recommendation engine can solve the data problem and provide a personalized experience for every visitor.

online recommendation engine

What is an Online Recommendation Engine?

You’re probably most familiar with online recommendation engines in the context of search engines.

You plug in a search query, the search engine scans millions – or billions – of webpages, and delivers custom recommendations to you.

Without digging too deep into search engine optimization, it’s worth pointing out that Google DOES take prior searches into account, monitoring which results users click for each query and how long they stay on each page. In some cases, the search engine may consider your own past search history as well.

The search engine algorithm uses machine learning to improve its results and offer the best answers for each query based on countless factors.

Then you also have online recommendation engines in the context of media platforms. Facebook, Netflix, Spotify, Pandora, and YouTube all offer personalized content recommendations using an algorithm and machine learning.

You may not realize, however, that you can also easily add an online recommendation engine to your website to personalize the visitor experience.

Instead of simply presenting your visitors with blog categories, you can use an algorithm to offer personalized suggestions based on the content they’ve already viewed, how long they read each piece of content, what they clicked next, and the behavior of previous visitors who behaved similarly.

Why Should You Add an Online Recommendation Engine to Your Website?

An online recommendation engine is beneficial both for your business and people visiting your website.

To Nurture Leads at Each Stage of the Sales Cycle

The biggest benefit to a content engine is that you can nurture leads literally as you sleep.

Here’s how lead nurturing used to go:

  • Hundreds of people visit your website to read your blogs.
  • A handful of them convert into leads.
  • You follow up with leads and learn about them.
  • You nurture them into completing a purchase.

This process is long, drawn-out, and frankly, outdated.

Today, you can start nurturing visitors in real-time as soon as they visit your website through the power of AI.

An estimated six to seven team members are involved in each sales process, on average. Everyone browsing your site has different roles at their company. It’s impossible to create effective content for all of them at each stage of the sales cycle.

An online content engine, however, can provide personalized content to every visitor more efficiently than a human ever could.

Not only that, but a content recommendation engine uses intent data to understand where each visitor is in the sales process and offers them relevant content. Leads can self-nurture as they read content on your site because the recommendation engine guides them through the sales process with its chosen content assets.

Remember that leads complete anywhere from 57% to 90% of the sales process entirely alone without speaking to anyone at your company, so giving them the tools to research and self-nurture is key to ROI.

To Learn About Your Audience

A personalized recommendation engine can also put more power in your hands to learn about your audience and their behavior so that you can create more relevant content.

When your visitors are offered personalized content recommendations, you can build a better understanding of their likes, needs, and dislikes.

Once a visitor hangs out on your site for some time browsing content, you can review your website traffic and see what they liked best. Use that information and build on it to create more content.

You can use this for two tiers of content: topics and types.

Remember that different visitors like unique types of content. 64% of B2Bs like podcasts, while 76% like infographics and 49% like video. These might seem like safe bets but you won’t know until you review your traffic.

Example of a content engine in action:

content engine

Source: Hushly

For Account-Based Marketing

When it comes to account-based marketing, an online recommendation engine is vital.

You could even argue that AI has made it possible for average businesses to build an ABM strategy at all. It’s simply not possible for most companies with limited budgets to have one without AI.

Account-based marketing requires particular care because your content needs to be hyper-relevant AND target your leads (and customers) at each stage of the sales process.

Instead of retroactively sorting through your lead database, drawing conclusions, analyzing the details, creating content, and choosing a delivery method to nurture, AI does everything while a visitor is still on your website. That’s right. It starts nurturing company-specific visitors before they ever convert into leads!

To Provide a Personalized Experience

85% of B2B buyers say they expect brands to provide a personalized experience from the very first interaction. If a brand doesn’t, they will likely dismiss the company.

That puts a lot of pressure on companies to personalize the buyer experience from the get-go.

Fortunately, an online recommendation engine makes it easy to start personalizing every point of contact on your site so you can provide the experience potential buyers expect.

When a potential lead visits your site, they may not know what they’d like to read or consume next. A personalized engine gives them recommendations akin to Netflix so they can binge at their leisure and find something that speaks to them without the effort of searching through categories.

Add an Online Recommendation Engine to Your Site Now

Hushly’s AI is easy to add to your site so you can offer your visitors a personalized online recommendation engine. Every visitor gets a completely personalized experience that guides them down the sales funnel – whether they’re a collected lead or random unknown browser.

online recommendation engine

3 Awesome Ways to Use Content-Based Recommendations in B2B

content-based recommendation

Content-based recommendations are everywhere we turn online.

Businesses need to consider that 59% of all B2B buyers are millennials. Now, millennials aren’t exactly the youngest in the game anymore. Many of them are pushing 40 this year.

However, it is important to remember that they’ve had personalized experiences everywhere they go online for several years.

They expect a personalized experience from your B2B site as well. The good news, however, is that millennial buyers are loyal when they find companies trustworthy: 96% told Salesforce they reward companies with their loyalty.

Using machine learning recommendations can help you create the digital experience they expect so you can build trust while improving your lead generation and conversion strategies as well.

content-based recommendation

How Do Content-Based Recommendations Work?

Different algorithms use machine learning to learn about human behavior and make personalized content recommendations. You’ve seen content-based recommendations in action on platforms like

  • Netflix: Records what you watch to completion, what others with similar tastes watched, and offers personalized suggestions.
  • Amazon: Follows what you bought, what customers with similar buying histories bought, and provides unique product recommendations.
  • Spotify: Offers personalized music recommendations based on your listening history and users with similar tastes.
  • Pandora: Uses qualities in the music to determine what kind of content you might like.

Pandora and Spotify use two totally different types of content-based recommendations. Spotify compares your behavior to similar users. Meanwhile, Pandora analyzes the music itself.

Most content-based recommendation systems use several algorithms to provide personalized suggestions – not just one!

  • Collaborative filtering: Collaborative filtering uses the idea that people who agreed in the past will agree in the future. It’s like when you ask your friend with similar music tastes for a recommendation. Using behavior from other website visitors and a current visitor, the algorithm provides unique recommendations for the visitor.
  • Content-based filtering: These algorithms scan content metadata and copy while analyzing a visitor’s behavior to determine what they might like to consume next.
  • Popularity assets model: This straightforward algorithm identifies the most popular pieces of content over a period of time.
  • Trending assets model: Differing from popularity, the trending model looks for surges in traffic and suggest these up-and-comers to visitors.
  • Important assets model: An algorithm monitors how many categories a piece of content belongs to, how many times someone consumed it, how long people stayed on the page, and other factors to determine its importance.

Keep in mind that some content-based recommendations allow users to input their own preferences as well. For example, when you sign up for an email list or app, it might ask for your topic preferences, gender, or age to make proper recommendations.

3 Ways to Use Content-Based Recommendations in B2B Marketing

You can easily add content-based recommendation systems to your B2B website to create an awesome experience for visitors and drive lead conversions. Here are a few options.

1. Adaptive Content Hubs

Let’s say you click on a blog post from LinkedIn. You finish reading it and want to read more content – what do you do?

Chances are, you either:

  • Hit the back button and return to LinkedIn
  • Click over to the website homepage
  • Browse different blog categories to find topics that interest you

An Adaptive Content Hub uses machine learning recommendations to take the burden of choice off web visitors. Instead of forcing them to sift through your blog categories and recent posts to find something interesting, an Adaptive Content Hub organizes everything based on categories and uses machine learning to offer personalized recommendations based on behavior.

Recent research shows that the average B2B consumes 13 pieces of content before making a decision, with the buying process taking about two weeks.

Keep in mind that different people prefer varying types of content. Some prefer video, others like blog posts, and some like podcasts. An Adaptive Content Hub helps them find the most relevant pieces of content based on their preferences and behavior.

2. Personalized Exit-Intent Popups

More B2Bs are browsing your website from smartphones than you think (or would be if it was more mobile-friendly).

Think with Google estimates that 70% of all B2B searches take place on mobile devices. Buyers spend between two and three hours researching from their phones every day.

It’s important to create an entirely mobile-friendly experience for them.

There’s nothing less mobile-friendly than a form. The last time anyone wants to fill out a form is when they’re trying to navigate away from your website.

Exit-intent popups can be effective tools for preventing bounces – but not forms.

Instead, you can use content-based recommendation tools to offer your visitors MORE personalized content based on their browsing behavior and prevent them from leaving your site.

Recommended Content

Source: Hushly

3. Self-Nurturing Landing Pages

When visitors reach the end of your landing pages, what happens?

They either convert or drop off, right? Considering that over 90% of visitors will never convert into leads, isn’t it time we rethink landing page design?

Self-nurturing landing pages give your readers personalized content recommendations when they get to the bottom of your articles instead of leaving the conversation up to chance.

You might already use “read more” internal links to personalize your content a bit by hand. However, an algorithm can take care of this faster and more effectively than humans because it uses machine learning and behavior.

Using this type of software on your page can increase your lead conversions by 51% because it helps them nurture as they browse.

Use Content Recommendations and Watch Leads Surge

Hushly makes it easy to add personalized content recommendations to your website using the power of machine learning technology. Make dead-end landing pages a thing of the past with content bingeing features and hyper-relevant content for every visitor – whether known or anonymous browsers.

Plus, the Hushly AI engine works with data you’re already collecting in real-time. You only pay for genuine leads – not using the platform or fake leads (because Hushly prevents those too).

content-based recommendation

What is Collaborative Filtering? What Every Marketer Needs to Know

what is collaborative filtering

Most B2B marketers understand that they need to incorporate personalization and AI into their marketing strategies.

However, they aren’t sure what AI looks like in practice and how it works.

Algorithms in your favorite apps like Spotify and Amazon use special techniques for organizing and offering content. That’s why Amazon will never recommend you hunting supplies if you don’t hunt or Billy Ray Cyrus if you don’t like country music (unless you’ve expressed interest in Old Town Road by Lil Nas X perhaps).

One of those algorithms is collaborative filtering. But what is collaborative filtering, how does it work, and why does it matter to B2B marketers? Let’s break it all down.

what is collaborative filtering

What is Collaborative Filtering? Collaborative Filtering Explained

Artificial intelligence uses machine learning to make decisions and supply personalized experiences to every visitor.

The secret behind personalization is the algorithm – several algorithms actually.

A collaborative filtering algorithm uses information based on earlier user behavior to make decisions for the current user.

Let’s say you’re looking for some new music. You have a trusted friend who shares your tastes in music. You tell them you want something that sounds like X, Y, and Z. Your friend might ask if you like A, B, and C and why or why not. They take various factors into account, such as the style, lyrics, and genre, to recommend a new band.

On a massive scale, that’s how Spotify functions. It uses huge datasets on listening history to make recommendations. You can also favorite, save, or thumbs-down artists or songs to help Spotify learn your tastes.

Websites and apps across every corner of the internet in every sector use collaborative filtering algorithms to personalize the user experience.

What is Collaborative Filtering Good for in B2B Marketing?

Marketers may not realize that major B2Bs like Microsoft, HubSpot, and Cisco are already using AI for personalization. AI isn’t the next big trend in B2B, and it’s already here.

You don’t need to understand all the finer details of how AI works, but you CAN learn the basics and how to apply them to your marketing strategy. Here are a few tools for incorporating collaborative filtering into your B2B marketing strategy.

Adaptive Content Recommendations

Did you know that buyers consume at least 13 pieces of content during the buying journey?

Considering six or seven people are involved in each decision on average, it’s impossible to know what topics and types of content they each need at the perfect time – let alone get it in front of their eyes.

Research shows that leads prefer certain types of content depending on their stage of the buying process. In the early stages, buyers like to consume websites, reviews, and reports. Further along, however, their attention shifts to vendor videos.

An Adaptive Content Hub intuitively knows which stage of the buying process a visitor is at because it analyzes their behavior and compares it to the behavior of previous visitors.

On the front end, every visitor gets personalized content recommendations from collaborative filtering based on their behavior, interests, and stage of the sales cycle.

Not only does this help improve their experience, but it also allows them to nurture themselves from the second they visit your website.

All you have to do is focus on creating the best content possible. The algorithm gets it in front of their face at the right time. Here’s an example in action:

Content Hub

Source: Hushly

Self-Nurturing Landing Pages and Content Bingeing

B2B landing pages without AI are boring and outdated – especially to younger visitors.

Research shows that 59% of all B2B buyers are millennials now. They’ve had access to personalized content everywhere they go online for years now.

Most landing pages aren’t designed for success. That’s why conversion rates are so low.

For one thing, most B2Bs rely on clunky forms to capture leads. Considering 70% of B2B searches happen on mobile devices, gated content with forms sets you up to drive away readers.

Self-nurturing landing pages with collaborative filtering offer a different solution.

Instead of presenting visitors with dead-end landing pages, you can give them the choice to binge your content with personalized recommendations. The collaborative filtering algorithm considers their behavior to offer relevant content based on the page they already viewed and how previous visitors behaved.

Keep in mind that buyers complete up to 90% of the sales process alone without ever contacting a sales team. Your website needs to do the heavy lifting by making your content as easy as possible to access. Self-nurturing landing pages make it happen.

Relevant and Engaging Exit-Intent Popups

There’s a huge trend right now in both B2B and B2C to bombard visitors with forms as they try to leave a website. When you want to leave a website, the last thing you want to do is give them your personal information.

This strategy is sad because exit-intent popups have so much potential to reduce bounce rates, draw visitors back in, and nurture leads.

Collaborative filtering algorithms are a game-changer here.

Instead of asking your visitors to fill out an annoying form, you can use an exit-intent popup to present them with personalized content recommendations based on the content they already viewed while they were on your website.

Of course, it also considers the behavior of other users as well before offering personalized content.

These algorithms don’t work in a vacuum, either. As a hybrid model, they use several other algorithms based on other factors like popularity, importance, and intent data to create the most relevant experience possible for everyone.

Visitors are much more likely to stick around and read more of your content when you’re throwing amazing content at them instead of an invasive form.

Use Personalized Recommendations to Skyrocket Leads

Hushly can help you take control of the power of AI to create personalized experiences for every visitor using data you’re already collecting. Instead of dead-end landing pages and unorganized blogs, Hushly uses collaborative filtering and other techniques to offer relevant content recommendations, whether a visitor is known or anonymous. The result? Leads jump by 51% guaranteed!

what is collaborative filtering