Building on the findings of the 2021 State of Marketing AI Report, the 2022 State of Marketing and Sales AI Report gave marketers (including those involved in sales activities) the opportunity to answer 14 survey questions, and rate the value of 50 sample marketing AI use cases. More than 600 marketers answered portions of the survey, and 371 answered all questions and use case ratings.
What we learned is that the marketing industry is demanding leaders who can provide on-the-job AI education that accelerates companies and careers. Marketers overwhelmingly believe AI will transform their work, and want to use it for increased personalization, revenue acceleration, and insight. But they’re held back by a number of factors, including a lack of training and a lack of clear ownership of AI adoption at organizations.
1. Marketers recognize the transformative impact AI will have on the marketing industry.
More than half of respondents (51 percent) said AI is critically important or very important to their marketing success over the next 12 months.
They also see AI having a massive impact on marketing teams in the next five years: 74 percent believe they will be intelligently automating more than a quarter of their tasks in the next five years. 41 percent of marketers anticipate half or more of their tasks will be automated by AI in the next five years.
2. Marketers are highly focused on using AI in the near term in three key areas: personalization, revenue acceleration, and getting actionable insights from data.
When asked what marketing outcomes they were achieving today with AI, respondents most often said they were creating personalized consumer experiences at scale (41 percent). Almost as many said they were accelerating revenue or getting more actionable insights from marketing data (both at 40 percent).
3. But the industry faces a major obstacle to achieving these attainable, real-world outcomes with AI: a significant lack of confidence in adopting and implementing AI.
Nearly half (45 percent) of all respondents say they’re still beginners when asked to classify their own AI knowledge and capabilities. Only 29 percent say they have high or very high confidence in evaluating the AI-powered marketing technology that makes their desired outcomes possible.
4. The reason for the lack of confidence in the industry is that most marketers lack adequate education and training.
Respondents are predominantly not afraid or wary of AI. When asked what was stopping them from adopting AI, only 19 percent cited a fear of AI. Instead, the biggest barrier by far was a lack of education and training, which was the top response cited by 63 percent of respondents. The second most common response was a lack of awareness of AI’s capabilities and use cases at 52 percent — up 6 points from 2021.
The reason for this is clear: 81 percent of respondents say their organization does not have or is still developing, AI-focused education and training. Only 11 percent say their companies have formal education and training programs.
5. But why is there such a gap in the AI-focused training holding marketers back? It comes down to the ownership of AI at companies.
Ownership of AI adoption and integration is highly fragmented across departments and roles with competing priorities.
33 percent of respondents say Chief Marketing Officers (CMOs) fully or partially own AI at their company. 19 percent say CTOs own it. 13 percent say Chief Digital Officers own it. 12 percent say Chief Data Officers own it. A full 29 percent said someone else outside of core C-suite roles owns AI. 18 percent don’t know who owns it.
This has led to an AI leadership vacuum, where marketers who recognize a future increasingly impacted by AI still lack the on-the-job guidance and education needed to adopt it.
6. CMOs and other C-suite roles have a major duty — and opportunity — to work together to develop internal training for a workforce hungry to deploy AI to achieve lasting competitive advantage.
According to IBM, more than 3,000 CEOs say technological factors were the number one concern for their enterprises over the next two to three years — and 60 percent are accelerating digital transformation, specifically in the areas of IoT, cloud computing, and AI.
This transformation will not, and cannot, happen without the more intelligent capabilities provided by AI-powered technology. The leaders that embrace AI will establish themselves as indispensable value-creators in their organizations — and the way to do that is by enabling their teams to do the same.
State of Marketing AI Methodology
The 2022 State of Marketing and Sales AI Report collected responses to 14 questions about AI and its role in marketing. Additionally, data on 50 different marketing AI use cases across five categories of marketing (Planning, Production, Promotion, Personalization, and Performance) was collected using Marketing AI Institute’s AI Score for MarketersTM assessment tool.
Respondents were not required to answer all questions or rate all use cases to submit their responses. A full 371 people answered all survey questions and completed the full assessment to rate 50 use cases. Some questions received upwards of 600 responses. (A new question was added in 2022, so the 371 people who answered all questions may have answered 13 questions or 14 questions depending on the survey completion date.)
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371 people answered all survey questions and completed the full assessment to rate 50 AI use cases.
The data presented in this report may reflect varying participation rates across different data points. Throughout the report, we clearly indicate the sample size of respondents for a particular answer set. In some places, percentages may add up to more than 100 percent, either due to multiple responses or the rounding up of percentages for ease of reading.
Respondents were gathered between June 1, 2021 and June 1, 2022. Respondents were marketed to by Marketing AI Institute and Drift via email, paid advertising, website popups, and social media.
This data builds on the 2021 State of Marketing AI Report from Marketing AI Institute and Drift, the first research of its kind to gain insight into how marketers understand, adopt, and scale AI. Most questions and use cases remain the same, in order to benchmark industry data year after year. Throughout the report, we clearly indicate new questions and use cases, or existing questions and use cases from 2021 that were altered in this year’s survey.
Survey respondents represented a diverse set of roles, marketing disciplines, and company sizes.
Roles
49 percent identified their roles as Director-level or above.
The highest percentage of respondents (22 percent) identified themselves as managers. The next highest identified role was CEO / President (17 percent). The C-suite as a whole comprised 32 percent of respondents.
Chief Marketing Officer comprised 11 percent of the respondents.
Areas of Marketing
59 percent are involved in content marketing, the highest percentage of respondents.
Respondents were asked about the areas of marketing in which they were involved at their organization and could select multiple marketing categories.
The leading category was content marketing at 59 percent. The next most common categories were: analytics (57 percent), email marketing (53 percent), social media marketing (52 percent), and communications (50 percent). More than one-third (35 percent) of respondents indicated they were involved in sales in some capacity.
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The leading category was content marketing at 59 percent. The next most common categories were: analytics (57 percent), email marketing (53 percent), social media marketing (52 percent), and communications (50 percent). More than one-third (35 percent) of respondents indicated they were involved in sales in some capacity.
Use case ratings throughout this report will reflect the fact that a majority of respondents do some work in content marketing, analytics, email marketing, social media marketing, and communications. Therefore, these use cases tend to be rated higher on average.
Marketing AI Adoption BY Industry
20% work in Professional Services, the highest percentage of respondents.
Professional services was the industry most commonly identified by respondents, comprising 20 percent of respondents. Software (12 percent), education (10 percent), and media (8 percent) were the next most common industries.
B2B vs. B2C Marketing AI Adoption
79 percent work in B2B.
When asked if their company was business-to-business (B2B) or business-to-consumer (B2C), 38 percent indicated they were exclusively in B2B, while 41 percent said they were in both B2B and B2C. Only 17 percent indicated they were exclusively B2C.
Given the overlap, 79 percent work either fully or partially in B2B, and 58 percent work either fully or partially in B2C.
Revenue
68 percent work at organizations with $10M or less in revenue.
More than two-thirds of respondents (68 percent) work at companies with $10M in revenue or less, which is virtually unchanged from 2021’s numbers. However, larger enterprises are significantly represented, with 23 percent of responses coming from individuals at companies with $50M or more in revenue.
Employees
62 percent work at organizations with less than 50 employees.
In line with revenue numbers, 62 percent of respondents work at organizations with less than 50 employees.
At the other end of the spectrum, 21 percent work at companies with 250 or more employees. And, of note, 9 percent work at large enterprises with 5,000 or more employees.
Location
The largest concentration of respondents came from the United States, with 41 percent of respondents.
Other top locations represented were India (11 percent), the United Kingdom (5 percent), Canada (5 percent), and Germany (3 percent).
Marketing AI Survey: Key Findings
As part of the State of Marketing AI Report, respondents were asked to answer 14 questions about their AI knowledge and how their organization uses AI in marketing. The questions were either multiple choice with a single answer possible or multiple choice with multiple answers possible.
Understanding of AI
45 percent of marketers classify themselves as AI beginners.
Q: “How would you classify your understanding of AI terminology and capabilities?”
Respondents were asked how they would classify their understanding of AI terminology and capabilities. A full 45 percent classify themselves at the beginner level, while 43 percent say they’re at an intermediate level. Just 12 percent say they are at an advanced level.
Compared to 2021’s numbers, it appears marketers are slowly edging out of the beginner phase of AI understanding. Last year, 50 percent said they were beginners compared to 45 percent this year.
Role in Evaluating and Purchasing Marketing AI Technology
32 percent of respondents are marketing AI technology decision-makers with purchasing authority.
Q: “Which best describes your involvement in evaluating and purchasing marketing technology?”
The survey showed that 32 percent of respondents are decision-makers with the authority and budget to purchase marketing technology in their organizations. An additional 21 percent are influencers who research and recommend solutions, the second-highest percentage of respondents.
Marketing AI Confidence Level
71 percent rate their confidence level evaluating AI-powered technology as medium, low, or none.
Q: “How would you rank your confidence evaluating AI-powered marketing technology?”
The most respondents (39 percent) rated their confidence in evaluating AI-powered marketing technology at a medium confidence level. 29 percent said they had low confidence. 19 percent said they had high confidence. And 3 percent said they had no confidence in evaluating AI-powered marketing technology.
Slightly more people are at the medium or low confidence level in 2022 versus 2021. In 2021, 69 percent of respondents rated their confidence level as medium, low, or none.
Additionally, 31 percent of respondents in 2021 said they had high or very high confidence. Today, that number is 29 percent of respondents.
Want to boost your confidence with AI?
AI’s Impact on Marketing Jobs
57 percent believe AI will create more marketing jobs than it eliminates.
Q: “What do you believe the net effect of AI will be on marketing jobs over the next decade?”
The majority of marketers are optimistic that AI will have a net positive effect on jobs, with 57 percent saying more jobs will be created by AI. 22 percent say AI will eliminate more jobs than it creates. 14 percent say they don’t know what AI’s impact on jobs will be, while 7 percent think AI won’t have a meaningful impact on jobs.
These numbers are virtually unchanged from 2021, indicating marketers remain confident year-over-year in AI’s positive impact on employment.
Stage of Marketing AI Transformation
51 percent of marketers are either piloting AI or scaling the technology.
Q: “Which stage of AI transformation best describes your marketing team?”
Respondents were asked which stage of marketing AI transformation best describes their marketing teams, and could choose multiple answers.
Respondents were most commonly in the understanding phase of marketing AI transformation (67 percent), where they were actively learning about AI, and exploring use cases and technologies. Slightly more than half (51 percent) were actually using AI, either by piloting the technology (36 percent) or scaling (15 percent).
Importance of AI to Marketing
51 percent of marketers say AI is either very important or critically important to their marketing success over the next 12 months.
Q: “How important is AI to the success of your marketing over the next 12 months?”
Slightly more than half of marketers (51 percent) say AI is either very important or critically important to the success of their marketing over the next 12 months. Another 33 percent say it is somewhat important. Just 6 percent say AI is not important at all to their marketing in the next year.
Marketing AI Outcomes
41 percent are creating personalized consumer experiences at scale with AI.
Q: “What outcomes is your marketing team achieving with AI TODAY? Choose all that apply.”
Respondents were asked which outcomes their teams were achieving with marketing AI today. They could select multiple answers.
Most commonly, respondents were using AI in marketing to create personalized consumer experiences at scale (41 percent). Almost as many (40 percent) were accelerating revenue growth or getting more actionable insights from marketing data (40 percent). Other common outcomes were reducing time spent on repetitive data-driven tasks (37 percent) and generating greater ROI on campaigns (36 percent).
Use of Intelligent Automation
74 percent believe they will be intelligently automating more than a quarter of their tasks in the next five years.
Q1: “What percentage of marketing tasks that your team performs are intelligently automated to some degree TODAY? (i.e. AI is applied to improve the efficiency and/or performance of the task.)”
Q2: What percentage of marketing tasks that your team performs do you believe will be intelligently automated to some degree in the NEXT FIVE YEARS? (i.e. AI will be applied to improve the efficiency and/or performance of the task.)”
Today, 77 percent of marketers say a quarter or less of their marketing tasks are intelligently automated to some degree.
However, over the next five years, 74 percent say more than a quarter of their tasks will be intelligently automated — indicating that a large majority of marketers expect increasing amounts of AI-powered automation in the near future. In fact, 41 percent of marketers anticipate half or more of their tasks will be automated in the next five years.
These are very similar percentages to 2021’s survey, which indicates marketers remain unchanged in their conviction that AI-powered automation will have a major impact on marketing work.
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74 percent believe they will be intelligently automating more than a quarter of their tasks in the next five years.
Barriers to Marketing AI Adoption
63 percent say a lack of education and training is a top barrier to AI adoption.
Q: “Which of the following do you consider barriers to the adoption of AI in your marketing? Choose all that apply.”
Respondents were asked about their barriers to AI adoption in their marketing and could choose multiple barriers.
The top barrier to AI adoption was a lack of education and training, with 63 percent of respondents citing it. Other major barriers included a lack of awareness (52 percent), lack of talent with the right skill sets (43 percent), and lack of strategy (42 percent).
Notably, only 19 percent of respondents cited a fear of AI and only 18 percent chose mistrust of AI as significant barriers to adoption.
In 2021, lack of education and training was also the top barrier, but for 70 percent of respondents versus 63 percent this year. Lack of awareness was the second-highest percentage and actually increased compared to last year (52 percent vs. 46 percent). Lack of resources also dropped a full 6 points from last year (40 percent in 2022 vs. 46 percent in 2021).
Marketing AI Education and Training
81 percent do not have internal AI-focused education and training currently developed.
Q: “Does your organization offer any AI-focused education and training for the marketing team?”
When asked if their organizations offered AI-focused education and training for the marketing team, 65 percent said no, and 16 percent said training was in development. Another 7 percent said they weren’t sure they had internal AI-focused education and training. Only 11 percent indicated that education and training existed in their organization today.
These numbers remained virtually unchanged from 2021’s data, indicating that companies have not acted in a meaningful way to resolve this education and training issue.
AI Ownership
33 percent say the Chief Marketing Officer owns the adoption and integration of AI technology for marketing, either solely or sharing ownership with other roles.
Q: “Who in your organization owns the adoption and integration of AI technology for marketing? Choose all that apply.”
19 percent of respondents said the Chief Marketing Officer had sole ownership of the adoption and integration of AI technology for marketing. Another 14 percent said the CMO co-owned AI with other roles. This makes CMOs the most common owner of AI, with 33 percent either solely owning AI or sharing ownership with other roles.
9 percent said the Chief Technology Officer had sole ownership. Another 10 percent said the CTO shared AI ownership with other roles. (19 percent total ownership.)
Notably, 18 percent weren’t sure who owned AI in their organization.
Marketing AI Use Cases: Key Findings
In November 2016, we launched Marketing AI Institute and published our first spotlight in which we ask the same questions of every company. (See Drift’s spotlight here.)
The insights gained from this research led to the creation of a new framework to help visualize and organize the marketing AI technology landscape – the 5Ps of Marketing AI.
- Planning: Building intelligent strategies
- Production: Creating intelligent content
- Personalization: Powering intelligent consumer experiences
- Promotion: Managing intelligent cross-channel promotions
- Performance: Turning data into intelligence
For this report, respondents were asked to rate 50 marketing AI use cases using the 5Ps of Marketing AI framework. Keep in mind, these are simply a collection of common use cases. There are hundreds, if not thousands, of potential use cases for AI in marketing.
For each of the 5Ps, respondents were asked the same question, “Assuming AI technology could be applied, how valuable would it be for your team to intelligently automate each of the use cases below?”
For each use case, respondents were asked to consider the potential time and money saved, and the increased probability of achieving business goals. Then, respondents were instructed to rate each use case on a 1-5 scale:
The resulting ratings offer unparalleled insights into how much marketers value the potential intelligent automation of more than four dozen use cases.
Across all marketing AI use cases, the average rating was 3.46 out of 5.00. The top 10 individual use cases by score across all 5Ps were:
- Measure return on investment (ROI) by channel, campaign, and overall. (3.95)
- Discover insights into top-performing content and campaigns. (3.87)
- Recommend highly targeted content to users in real-time. (3.81)
- Adapt audience targeting based on behavior and lookalike analysis. (3.79)
- Optimize website content for search engines. (3.77)
- Create data-driven content. (3.77)
- Forecast campaign results based on predictive analysis. (3.73)
- Predict winning creative (e.g. digital ads, landing pages, CTAs) before launch without A/B testing. (3.72)
- Create performance reports based on marketing data and analytics. (3.71)
- Construct buyer personas based on needs, goals, intent, and behavior. (3.68)
Out of the top 10 marketing AI use cases, four were classified as dealing with content marketing. An additional four were classified as analytics use cases.
The five lowest-rated use cases included:
- Translate content into multiple languages. (3.13)
- Predict customer churn. (3.07)
- Transcribe audio (calls, meetings, podcasts, webinars) into text. (2.99)
- Formulate pricing strategies to maximize profitability. (2.98)
- Allocate and adjust marketing budgets. (2.94)
It is important to remember that use cases are subjective. The majority of respondents do at least some work in content marketing, analytics, email marketing, social media marketing, and communications, which may account for the use cases that get rated highest and lowest. A low-ranked use case may have the potential to unlock enormous value for individuals who work in areas of marketing different from the respondents in this report.
Marketing AI Use Cases by Category
As a part of the survey, respondents were given an overall AI Score based on the total value of their ratings, divided by 250, which is the total possible score if you rated every use case a 5 (i.e. 50 use cases with a score of up to 5 for each use case). This score is a reliable proxy for understanding AI’s potential at your organization across each of the 5Ps, as well as an individual’s overall need for AI in their marketing.
Across all respondents, the average total AI Score was 69 percent, indicating AI holds overall high potential for the marketing activities of those surveyed. We also broke down the AI Score for each individual use case category.
Planning
The average AI Score across Planning use cases was 66 percent, slightly below the overall average. The average use case rating in this category was 3.34.
The top three use cases rated highly by respondents in the Planning section were:
- Construct buyer personas based on needs, goals, intent, and behavior. (3.68)
- Analyze existing online content for gaps and opportunities. (3.68)
- Choose keywords and topic clusters for content optimization. (3.64)
The three lowest-rated use cases were:
- Predict customer churn. (3.07)
- Formulate pricing strategies to maximize profitability. (2.98)
- Allocate and adjust marketing budgets. (2.94)
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Average AI Score across Planning use cases was 66%
Production
Creating intelligent content.
The average AI Score across Production use cases was 69 percent, right in line with the overall average. The average use case rating in this category was 3.43.
The top three use cases rated highly by respondents in the Production section were:
- Optimize website content for search engines. (3.77)
- Create data-driven content. (3.77)
- Predict content performance before deployment. (3.67)
The three lowest-rated use cases were:
- Write creative briefs and blog post drafts. (3.23)
- Translate content into multiple languages. (3.13)
- Transcribe audio (calls, meetings, podcasts, webinars) into text. (2.99)
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Average AI Score across Production use cases was 69%
Personalization
Powering intelligent consumer experiences.
The average AI Score across Personalization use cases was 69 percent, right in line with the overall average. The average use case rating in this category was 3.45.
The top three use cases rated highly by respondents in the Personalization section were:
- Recommend highly targeted content to users in real-time. (3.81)
- Determine offers that will motivate individuals to action. (3.55)
- Present individualized experiences on the web and/or in-app. (3.48)
The three lowest-rated use cases were:
- Customize email nurturing workflows and content. (3.35)
- Engage website visitors in conversations through chatbots that learn and evolve. (3.27)
- Optimize email send time at an individual recipient level. (3.25)
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Average AI Score across Personalization use cases was 69%
Promotion
Managing intelligent cross-channel promotions.
The average AI Score across Promotion use cases was 71 percent, above average. The average use case rating in this category was 3.56.
The top three use cases rated highly by respondents in the Promotion section were:
- Adapt audience targeting based on behavior and lookalike analysis. (3.79)
- Predict winning creative (e.g. digital ads, landing pages, CTAs) before launch without A/B testing. (3.72)
- Deliver individualized content experiences across channels. (3.66)
The three lowest-rated use cases were:
- Adjust digital ad spend in real-time based on performance. (3.49)
- Improve email deliverability. (3.42)
- Schedule social shares for optimal impressions and engagement. (3.35)
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Average AI Score across Promotion use cases was 71%
Performance
Turning data into intelligence.
The average AI Score across Performance use cases was 73 percent, above average and the highest average AI Score across categories. The average use case rating in this category was 3.63.
The top three use cases rated highly by respondents in the Performance section were:
- Measure return on investment (ROI) by channel, campaign, and overall. (3.95)
- Discover insights into top-performing content and campaigns. (3.87)
- Forecast campaign results based on predictive analysis. (3.73)
The three lowest-rated use cases were:
- Predict revenue potential for accounts at different stages of the buyer journey. (3.55)
- Determine which teams, channels, and campaigns get credit for conversions. (3.39)
- Monitor and evaluate brand mentions from media and influencers. (3.31)
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Average AI Score across Performance use cases was 73%
When asked “In which areas are you involved?,” 35 percent of this year’s survey respondents said they were involved in sales. This doesn’t mean 35 percent of respondents are salespeople, just involved in sales in some way, as respondents could select multiple answers. We call these “sales-involved” roles, and this cohort contains unique insight into how AI is understood and used by professionals working with sales.
Understanding of AI
Respondents involved in sales are ahead when it comes to understanding AI terminology and capabilities.
Q: “How would you classify your understanding of AI terminology and capabilities?”
Sales-involved respondents were asked how they would classify their understanding of AI terminology and capabilities. 48 percent said they were at an intermediate level — a full 5 points higher than the percentage of all respondents. Additionally, 39 percent of sales-involved respondents said they were beginners, compared to 45 percent in the overall survey population.
Sales-Involved AI Confidence Level
Respondents involved in sales are more confident in their ability to evaluate AI-powered marketing technology.
Q: “How would you rank your confidence evaluating AI-powered marketing technology?”
37 percent of sales-involved respondents said their confidence in evaluating AI-powered marketing technology was either high or very high, compared to just 29 percent who answered the same in the overall survey population. They also had fewer responses of low confidence (26 percent vs. 29 percent overall) and medium confidence (36 percent vs. 39 percent overall).
AI Ownership
40 percent say the Chief Marketing Officer owns the adoption and integration of AI technology for marketing, either solely or sharing ownership with other roles.
Q: “Who in your organization owns the adoption and integration of AI technology for marketing? Choose all that apply.”
40 percent of sales-involved respondents said the Chief Marketing Officer had sole or shared ownership of the adoption and integration of AI technology for marketing. This is somewhat higher than the general survey population, in which 33 percent said the same. (In both cases, responses are likely skewed towards CMOs, since the survey population is marketers.)
Additionally, the proportion of respondents who didn’t know who owned AI at their company was lower, with 14 percent of sales-involved respondents saying they weren’t sure versus 18 percent overall.
Top AI Use Cases
The top 10 individual use cases by score across all 5Ps for sales-involved respondents were:
- Measure return on investment (ROI) by channel, campaign, and overall. (4.09)
- Recommend highly targeted content to users in real-time. (3.98)
- Adapt audience targeting based on behavior and lookalike analysis. (3.98)
- Optimize website content for search engines. (3.96)
- Predict winning creative (e.g. digital ads, landing pages, CTAs) before launch without A/B testing. (3.95)
- Forecast campaign results based on predictive analysis. (3.94)
- Create data-driven content. (3.94)
- Discover insights into top-performing content and campaigns. (3.93)
- Construct buyer personas based on needs, goals, intent, and behavior. (3.89)
- Predict revenue potential for accounts at different stages of the buyer journey. (3.88)
The five lowest-rated use cases included:
- Formulate pricing strategies to maximize profitability. (3.21)
- Predict customer churn. (3.16)
- Allocate and adjust marketing budgets. (3.12)
- Transcribe audio (calls, meetings, podcasts, webinars) into text. (3.10)
- Translate content into multiple languages. (2.96)
Overall, sales-involved respondents scored slightly higher averages across all categories in the 5Ps framework, and overall.
The Rise of Conversational AI
You can’t tell the story of AI in marketing and sales without talking about Conversational AI. With chatbots and other forms of Conversational AI, marketers and salespeople can participate in 1-to-1 conversations at scale, 24/7/365. And Conversational AI gives consumers the freedom to connect with companies on their own terms — whenever they want.
It’s never been more important to do so.
In the last 24 months, the digitization of customer interactions has sped up by three years, according to McKinsey. Compared to 2021, executives are three times as likely to say the majority of their brands’ customer interactions are digital.
This doesn’t just mean brands are selling more — and more often — online. It means the entire customer journey has gone digital. Thanks to the internet, consumers have increasingly taken charge of their journeys with brands. Because of the COVID-19 pandemic, they’re now entirely in the driver’s seat. This new normal means consumers demand always-on, self-directed service and experiences, and failing to deliver has serious consequences.
Nearly one-third of potential customers say they’ll stop doing business with a brand they love after one bad experience. After more than one bad experience? That number rises to almost 60 percent who would walk away, according to PwC.
Yet few brands have the resources, talent, or know-how to spin up — and manage — a 24/7 marketing and sales engagement machine. To help, brands have turned to Conversational AI as a critical necessity to scale digital engagement in a few major ways.
AI Chatbots on Websites
For most marketers, chatbots jump to mind first when they think of AI and Conversational Marketing — and for good reason.
When embedded on a website, chatbots can save marketers time, augment our capabilities and even unlock new lead generation channels.
Specifically, AI chatbots can:
- Automatically answer common questions in real-time. For standard questions your site visitors ask regularly, chatbots can be programmed to answer those questions how you’d like at all hours of the day.
- Answer a broad range of questions using content published on your website. Emerging AI solutions can go beyond answering set, common questions.
- Eliminate or supplement lead gen forms. Marketers know this: Forms create friction. Drift, in classic “practice what you preach” form, eliminated all of its forms in 2016. They instead used their conversations tool and chatbot to generate leads. The result: More leads (+15%), a faster sales cycle (3 days from conversation to demo), and less wasted time (AI handles 50% of all conversations). Rather than relying on a form to halt progress, chatbots increase the number of conversations brands have with site visitors and create more sales conversations.
- Schedule sales meetings. Not only can a chatbot do more typical top-of-the-funnel work, it can actually book sales calls. If linked with the team’s calendar, once the chatbot’s “conversation” has progressed, AI-powered bots can offer times and automatically add meetings to your calendar.
AI Email Assistants
When you see a website chatbot, you’ll notice that most have a robot-like name, immediately signaling to visitors that they’re messaging a bot, not a human.
When communicating through email, conversational messaging companies have created what they call “AI sales assistants,” which act like humans to engage in conversations promptly, professionally, and persistently. The email address will appear like a coworker, talk like one, and even have a human name.
These AI sales assistants cannot replace the work of your sales team. Rather, these platforms amplify your capabilities and can create opportunities from leads that would have otherwise remained dormant.
AI sales assistants enable companies to:
- Engage cold leads. If you’re like most businesses, there is a database of old contacts that you don’t have time to reengage. That’s where AI sales assistants come in.
- Pursue less qualified or lower priority leads. You might have a database full of potential leads that your team will never have time to contact. An AI sales assistant executes sales outreach to see which of these leads might be more qualified than you thought.
- Pass qualified or hot leads over to sales. Once a conversation with the AI sales assistant progresses, the tool will identify if a lead is ready for a sales call or meeting. At that point, your human team takes over, without having wasted a minute on the leads that never amounted to anything.
- Execute consistent follow-ups with buyers. Studies show that several touchpoints are necessary to effectively convert prospects into customers. Always-on Conversational AI offers marketers and salespeople the opportunity to have more meaningful conversations with qualified buyers, not send hundreds of emails that lead nowhere.
AI Messenger Assistants
Creative marketers and salespeople across all industries are unlocking new possibilities with AI and chatbots. The following use cases show how AI can actually make brands seem more human and personal, not less. With AI messengers, marketers and salespeople can:
- Engage in automated conversations to make personalized recommendations. Imagine offering a unique experience that is tailored to each individual buyer. With AI, these interactions are 100% automated and make hyper-personalization at scale a reality.
- Educate customers and learn more about them. Building on the advantages of the last point, messenger bots can educate consumers as they answer your questions — creating value for the consumer as you learn about them. This feels like a human conversation for the consumer, and is offered at a capacity that would require a massive team to do without AI.
Drift Conversational AI
With Drift Conversational AI, customers can ask open-ended questions in chat — and get answers in real-time. Conversational AI is the powerful technology behind the Drift Conversation Cloud, which helps businesses engage with buyers in a personalized way at every stage of the buying journey. Conversational AI guides visitors on a personalized journey to deliver better engagement and customer experiences. It enables flexible, human-like conversations, letting visitors voice their intent in their own words. They can find answers to their questions, get personalized recommendations, or book a sales meeting — 24/7. Conversational AI gives your buyers conversations without limitations. Get a demo today.
