Generating high-quality leads can be a difficult, time-intensive process. AI tools can help reduce some of the manual work, saving you valuable time and resources.
Lucky for you, Podium has just the right tool for this! Podium’s conversational AI is outcome-driven – it doesn’t just respond to inbound leads it guides conversations toward a specific goal, such as a sale or booking. Unlike other AI systems that focus on providing correct responses, Podium aims to drive specific customer actions to grow your business. Speed to lead is critical in today’s fast-paced market, and Podium offers an unparalleled advantage by ensuring businesses engage with leads within a couple of minutes—guaranteed.
This article will provide a guide on how to leverage AI to generate high-quality leads. It will also highlight some of the pros and cons of these tools, including Podium’s AI assistant, and how they can help you drive more sales and grow your business faster.
Why Use AI for Lead Generation
Using AI for lead generation can help your organization reduce manual work, improve targeting and personalization, make data-driven choices, and scale your efforts. Let’s take a closer look at these compelling reasons to use AI for lead generation.
1. Enhanced Efficiency
AI can automate many lead generation tasks, from lead scoring to answering routine questions via chatbots or social media. This can save your organization a significant amount of time and resources, allowing your sales, marketing, and support teams to focus on more complex aspects of the sales process and other higher-level priorities.
For example, consider that 83% of consumers expect companies to respond to social media comments within 24 hours or less. To meet this consumer preference without AI, you’d need humans working around the clock. However, leveraging AI for social media management could enable your brand to respond automatically to comments on posts.
Podium’s AI Employee guarantees your business engages with leads within a couple of minutes; during peak hours, off hours, and every hour in between.
2. Personalized Outreach
There are two applications of AI that can help you personalize your outreach to prospects, improving your chances of converting. First, AI algorithms can segment and categorize leads based on various criteria, such as demographics, behavior, and interests. You can then create highly targeted marketing campaigns for different segments.
For these campaigns, you can also use AI to tailor your messaging and content to individual leads or segments of your audience, creating a more personalized and engaging experience. This personalization increases the likelihood of conversion.
3. Data-Driven Insights
AI can analyze larger volumes of data much faster and more efficiently than human analysts to identify patterns and trends that may inform your decision-making.
For example, AI can help you make more accurate predictions about which leads are most likely to convert into paying customers based on historical data and real-time interactions. This data can help your teams concentrate their efforts on leads with the highest likelihood of becoming customers.
4. Scalability
Since AI can handle a large volume of leads simultaneously, it will enable your organization to scale your lead generation efforts without proportionally increasing your human workforce.
Take AI-powered chatbots for example. As the volume of leads increases, chatbots can handle the load without the need for additional human resources. This makes chatbots an efficient and scalable way to engage with potential customers, gather important information, and move them along the sales funnel.
10 Lead Generation Tactics That Involve AI
Below are 10 ways to use AI for lead generation. Each tactic is explained in detail, with examples.
1. Chatbots
Implementing chatbots on your website, app, or messaging channels (such as Facebook Messenger) can help you provide instant responses to prospects 24/7. This not only helps provide an excellent experience and immediately starts to build trust—it can also present valuable conversion opportunities. For example, a chatbot might help a prospect schedule an appointment, effectively making them a lead without any human intervention.
A chatbot can persuade prospects to provide their contact information for reasons beyond appointment scheduling as well. For example, if the chatbot can’t answer the prospect’s question, they may ask for their contact info so a human rep can follow up on the inquiry.
With Podium Webchat, you can skip this step. The conversation is immediately taken to text so it doesn’t end when customers leave your site and so that you automatically have their name and phone number. If you’re interested in learning more, see Webchat in action on your site.
2. Conversational AI
Conversational AI can also help you generate high-quality leads. While chatbots respond to prospects and customers with predefined answers based on programmed rules, conversational AI uses a combination of natural language processing, foundation models, and machine learning to simulate human conversation. As a result, conversational AI can help engage prospects in natural and personalized conversations and convince them to convert.
For example, a conversational AI tool can provide personalized recommendations based on their input and past interactions, which will improve the chances of them making a purchase. Amazon’s voice assistant Alexa is a well-known example. It can provide personalized recommendations for products, music, and more based on user preferences and past conversations.
3. Behavioral Analysis
AI tools can provide rich behavioral analysis that helps improve your lead generation efforts. Utilize AI tools to monitor and analyze user behavior on your website and other digital platforms, then use this data to understand customer preferences, interests, and pain points and better tailor your content and marketing campaigns to them.
For example, U.K. retailer Marks & Spencer used behavioral analysis to understand common pain points in the buyer’s journey. They discovered that issues with promotion codes were resulting in abandoned carts and implemented another AI strategy in response. Their virtual assistant automatically appears when prospects have entered a discount code incorrectly twice and takes them through a series of multiple-choice questions to resolve the issue.
4. Lead Scoring
Traditional lead scoring can be tedious, time-consuming, and limited since it relies on a limited set of predefined criteria. Leveraging AI for lead scoring can help solve these issues and maximize your lead generation efforts.
Use AI tools to analyze lead data and assign scores based on behavior, demographics, and interactions. This helps prioritize leads for sales outreach so salespeople can focus on leads with the highest conversion potential rather than waste their time having unproductive or ineffective conversations.
5. Content Personalization
Emails, landing pages, and other marketing collateral with generic content are less likely to convert prospects. You can use AI tools to segment your leads and personalize content for these different segments. You can use generative AI to further tailor your content based on data signals about the context and intent of your audience, such as their location, time of day, or stage in the customer journey.
By providing more relevant and timely communications to groups of users, you’re more likely to see improved conversion rates.
6. Automated Review Invites
According to a survey by Clutch, 94% of B2B buyers have used an online review to help make a B2B buying decision. Additionally, nearly half of B2B buyers (47%) read at least six reviews in the process.
To generate more reviews in less time, you can use AI to automate your process for sending review invites. For example, you can use AI to segment your customers based on factors like purchase history, behavior, and demographics to identify the best customers to send review invites to. You can also use AI to determine the best time to send review invites based on a customer’s interaction history. It can also personalize the message to make it more engaging and relevant.
Learn how Podium’s review software and Google Review Link Generator can also help you quickly and easily generate reviews to feature on your lead generation website. You can also generate some AI-powered, personalize Review responses here.
7. Social Media Listening
You can also leverage AI for social media listening to generate high-quality leads. AI-powered tools can “listen” on social media channels for mentions, comments, and discussions related to your industry or products by scanning and analyzing the large volumes of data generated from social media channels, blogs, forums, and other relevant online sources. This can help you source opportunities to attract or engage with customers and potential leads in real-time.
Take the viral exchange between Skyscanner, an airline search engine that compares millions of flights to find the cheapest deals, and a user who posted a screenshot on Facebook about one result with a 47-year layover on a trip from New Zealand to London. The user wrote, “Just wondering what you’d recommend I do during the 47-year layover your website has suggested?” Skyscanner promptly responded with some funny suggestions for what to do during an extended layover in Bangkok and also said that they’d have someone look into this glitch. The response went viral and led to some Facebook users posting that they’d now use Skyscanner.
Leveraging AI for social media listening can also help you gain valuable insights into your customers’ sentiments, preferences, and trends, which can help inform your marketing campaigns and other lead-generation efforts.
8. A/B testing optimization
AI can help you optimize the A/B testing process. For example, the popular A/B testing tool VWO Testing now integrates with Open AI’s GPT-3.5 Turbo API to enable customers to use AI-generated copy as variations for their website copy and deploy them in A/B tests in less time.
You can not only use AI to help generate multiple versions of your content with different tones, styles, or formats — you can also use AI to run A/B tests of these variations to identify what resonates best with your customers.
9. Dynamic content generation
AI models can use a broad set of signals about customer intent including real-time behaviors, prior purchases, preferences, and interests of similar customers in order to dynamically generate content that is most likely to appeal to them. For website landing pages, for example, AI can be used to dynamically select the images and messaging that will be most likely to convert a prospect. The same is true of ads.
With Google Ads, for example, text ads for a landing page can be completely or partially generated dynamically to match user search queries. Facebook also offers dynamic display ads for remarketing campaigns. For example, say you own an ecommerce site, and use Facebook as one of your social media channels. You could retarget any users who visited your Facebook page and displayed interest in a product but did not make a purchase with a dynamically generated ad of that product. Ads that are strategically selected based on prior user interests are more likely to convert prospects into leads.
10. Predictive analytics
Predictive analysis uses artificial intelligence as well as data analysis and statistical models to find patterns in historic or current data that might predict future consumer behavior or trends. In other words, the goal of predictive analytics is to use data to answer the question “what will happen?” Predictive analytics can significantly improve your lead generation efforts by increasing up- and cross-selling opportunities based on customer profiles, forecasting future demand and sales, and more.
For example, you can use predictive analytics to identify the factors that are most strongly associated with high-quality leads, like demographic data, purchase history, and website behavior, and then identify new leads who exhibit similar behavior. Focusing on those leads can help increase your chances of growing your revenue and customer base.
In addition to lead scoring, you can use predictive analytics to better understand what products or services to promote to which customers at what time. Amazon, for example, is well-known for using predictive analytics to provide personalized recommendations to users that are more likely to lead to sales. Its software—called the Collaborative Filtering Engine (CFE)—uses several data points about the user’s past behavior, including items they added to their wishlist or saved to their cart, as well as current data, like product reviews and the most searched products, to make these recommendations.
For example, if a consumer is browsing a KitchenAid mixer, they’ll see recommendations to buy a beater and slicer/shredder as well. Because these three items have been frequently bought together in the past, Amazon is predicting that future consumers may also buy these items together and provides an easy option to add all three items to their cart with one click of a button.
4 AI Tools for Lead Generation and Sales Prospecting
AI tools can help businesses drive qualified leads. Take a look at some tools below and the pros and cons of each.
1. Podium
Podium’s AI Assistant can help businesses more quickly and easily respond to reviews as well as frequently asked questions or other inquiries via web chat. It can also help you create tailored and personalized messages in bulk so you can create and send marketing promotions, appointment confirmations, and review invitations in seconds.
Pros
- Can be used for multiple lead-generation strategies
- Manage, respond to, and consolidate all of your leads in one place
- Part of an all-in-one communications solution
Cons
- Missing some functionality, like being able to search messages by keyword
- No spam filtering functionality
Don’t let your competition beat you to new leads. Try Podium’s AI Employee today.
