The average sales representative spends less than a third of their week actually selling.
The rest of their valuable time is eaten up by planning, forecasting, researching prospects, and sitting in meetings. And while these tasks are important, they detract from the time reps can spend closing deals.
Fortunately, artificial intelligence (AI) is now changing that. Comprehensive ai sales assistant tools like AI Sales OS by Copy.ai can be used to automate repetitive tasks, research and predict best-fit prospects, hyper-personalized sales email and outreach, and dramatically lower the amount of time reps spend doing manual busywork.
Whether sales teams are using chatbots and AI sales assistants to scale their self-serve functions, or tools like Copy.ai to improve go-to-market velocity through workflows and tools that increase efficiency and lower bloat, AI sales automation is where the world is placing its bets for 2024 and onwards.
In this guide, we will:
Let's dive in!
Artificial intelligence (AI) refers to technology that includes processes like machine learning, natural language processing, and deep learning. In the context of AI for sales, these capabilities are used to make sales professionals’ jobs easier by automating tasks, crunching numbers, surfacing opportunities, and suggesting sales copy.
But how does AI work?
Just like a Sales Development Representative (SDR) might learn to write great cold pitch emails by studying a ton of examples and learning from a mentor, AI tools learn by being fed a tremendous amount of data. The platform then learns from these inputs to create outputs of its own, often detecting patterns that humans might miss — which can lead to the discovery of new opportunities, improved sales communication, and the highlighting of helpful customer data.
But AI and machine learning models don’t just produce new outputs — they’re specifically trained so that they continually improve their results. When these algorithms are being trained, they’re not just fed existing SDR pitches.
They’re also given the results of each of these pitches, along with huge data sets on the customers being pitched, so that they learn which types of content work best. They then tailor the pitches they write based on best results, the type of customer being pitched, the platform used for messaging, and the product being sold.
This same learning model is also used for lead generation and scoring, sales forecasting, and conversational AI.
Of course, SDRs and sales reps may modify their approaches based on their past experiences and the customer persona they’re pitching. But, far too often, these choices are based solely on hunches, which can be wrong. AI apps make decisions based solely on data, which is far more likely to lead to successful results compared to that of instinct and hunches.
Since computers have incredibly strong processing power, they can also churn out these outputs in a matter of seconds compared to your average SDR or sales rep. By completing routine tasks at a phenomenal speed in real time, AI can help salespeople accomplish more in less time. AI makes it easy to deliver an exceptional customer experience and make strategic decisions.
Before the great AI revolution, salespeople were buried in tedious tasks that took away from the one thing they were hired to do: build relationships. Here's a glimpse at the busy day of a sales rep before AI:
This left little time to focus on the key quality sales people are hired for: relationship-building for the long-term. However, according to Salesforce’s 2022 State of Sales report, high-performing sales reps were nearly two times more likely to use AI than underperformers.
This shouldn’t be surprising, considering the ever-growing list of opportunities that arise when adding AI to your workflow.
Artificial intelligence (AI) brings together machine learning, natural language processing, and deep learning to transform how we interact with technology.. In AI for sales, these capabilities are used to make sales professionals’ jobs easier — by automating tasks, crunching numbers, surfacing opportunities, and making recommendations for copy, insights, and ideation.
What makes AI feel like magic in the sales process? Its capacity to “learn on the job.”
Ever know an SDR who spends hours perfecting cold outreach emails, sifting through countless examples or seeking guidance from mentors? Well, AI systems do something similar—they learn by:
Because AI is continuously trained on massive databanks, they tend to excel with things like pattern-finding and statistics (ie. win/lost), and are able to compute all of this within seconds.
With AI tools in place, all SDRs have to do is ask the right questions, set up the most efficient automations, and make use of the most valuable workflows for them.
By using the power of AI sales assistants for automating repetitive tasks (like call transcription, analysis, and summaries), reps free up their time do more of the “human” part of their own sales jobs: building rapport with customers and prospects over the long-term, so they’re viewed more as consultants than pushy salespeople.
AI technology can significantly enhance the productivity and efficiency of sales teams by automating manual tasks.
With AI, sales representatives can focus their expertise on closing deals while mundane tasks like data entry, lead enrichment, and scheduling are handled seamlessly. By freeing up time, sales teams can cover more ground, further customer relationships, engage with more prospects, and increase their chances of achieving revenue targets.
AI-generated analytics can help sales teams gain a deep understanding of customer preferences, pain points, and buying signals.
With this information, sales representatives can tailor their approach and offer personalized solutions to customers.
AI can also help sales teams make data-driven decisions (thanks to its processing power and strength in recognizing patterns in mass amounts of data), optimize sales strategies, and identify trends and patterns that would otherwise go unnoticed.
AI can help sales teams achieve higher conversion rates by identifying the most promising leads and providing sales representatives with valuable insights on how to engage and convert these prospects effectively.
Alternatively, AI-powered chatbots and virtual assistants can also assist sales managers in nurturing leads, answering inquiries, and guiding customers towards purchase decisions.
AI automation streamlines time-consuming tasks like manual data entry, report generation, and follow-up emails.
With this newfound efficiency, sales teams can operate at a faster pace with greater accuracy and consistency across tasks. This allows sales representatives to respond promptly to customer inquiries, capitalize on time-sensitive opportunities, and stay ahead of competitors.
AI-powered chatbots and virtual assistants can provide 24/7 availability, enhancing customer satisfaction by offering prompt and personalized service regardless of the time or day.
This availability allows sales teams to capture leads and address customer needs at any hour, establishing a reputation for exceptional service and providing a competitive edge in the B2B sales landscape.
Also, AI sales assistants (like AI Sales OS by Copy.ai) run workflows automatically in the background 24/7: transcribing, assessing, analyzing, and providing insights while you sleep, so that when you get to your desk, you have valuable data to take action on with prospects.
AI technology is a powerful tool for sales teams, and it can help with just about any part of the sales process. With the help of AI, teams can now use data to make smarter decisions about their outreach and communication, sales forecasting, customer segmentation, and lead scoring — and these days, AI can even engage in conversation and make product recommendations for customers. That sounds amazing, right?
AI can analyze data from various sources to identify potential leads that are more likely to convert. This helps sales teams focus their efforts on high-value prospects and improves their prospecting efficiency.
AI Sales OS has prospecting workflows that help you:
AI-powered sales tools can gather and analyze data about competitors, such as pricing, product features, customer reviews, and social media presence. This information enables sales teams to identify unique selling points, develop effective strategies, and update battlecards to stay ahead of the competition.
AI Sales OS has competitive analysis workflows that help you:
AI can help sales teams personalize their outreach efforts by analyzing customer data and generating insights from customer interactions. This enables sales representatives to tailor their messaging, recommendations, and offers to individual customers, increasing the chances of success.
AI Sales OS has personalized outreach workflows that help you:
Don’t you think that makes outreach a lot more effective?
AI algorithms can assess the likelihood of a lead converting into a customer based on various factors, such as behavior, demographics, and engagement. This helps sales teams prioritize leads and tailor their approach accordingly.
AI Sales OS has lead scoring workflows that help you:
AI can automate tasks related to CRM (customer relationship management), such as data entry and updating customer records. This streamlines the process, reduces manual effort, and improves data accuracy and hygiene.
AI Sales OS has CRM management workflows that help you:
AI can analyze customer preferences and behavior to recommend relevant content, such as articles, blog posts, or product recommendations. This helps sales teams engage customers with personalized content at various stages of the sales process.
AI Sales OS has content personalization workflows that help you:
AI-powered tools can analyze sales calls, emails, and meetings to provide feedback and suggestions to sales representatives. This helps improve their sales techniques, communication skills, and overall sales performance.
AI Sales OS has sales coaching workflows that help you:
It’s like having a coach with you every step of the way!
Integrating AI and automation into your sales processes can deliver significant benefits, but it's important to approach implementation strategically.
Imagine this: A sales team, stuck in the grind of manual tasks, feeling the pressure of an ever-growing pipeline. Their time spent on repetitive activities is robbing them of opportunities to engage with prospects, and it’s starting to show in the results. But then, they decide to make a change.
Here’s how they do it.
The first step on their journey is to assess their current sales processes and metrics to identify any weaknesses or bottlenecks that could benefit from AI and automation.
The question lingers around: Where is the team spending the most time? Where are the results lagging? What are the current bottlenecks in the sales process? What are the time-consuming, repetitive tasks that are most prone to errors?
The head of sales sees the same pattern: research, lead generation, cold outreach, and follow-up calls are all taking too much time and yielding suboptimal results. There has to be a better way.
And, this is where AI comes in.
Based on these findings, explore where sales AI could potentially be of use. For instance, if SDRs’ cold emails aren’t getting the results they should and that the account managers are spending too much time answering emails, an AI content generator could hit two birds with one stone.
Each company’s assessment and opportunities for automation will be different, but here are some examples of sales tasks that are primed for AI:
They begin to see the potential of what AI could do for them.
With the problems clearly identified, the sales team starts researching AI tools and platforms to help them optimize their workflows. The market is full of options, but they need the right solutions.
They thoroughly research different AI sales tools and platforms available in the market. Evaluate their features, integrations, ease of use, and scalability to find the solution that aligns best with the team's needs and goals. They consider factors such as data security, customer support and training, and compatibility with their existing systems.
They stumble upon a few AI solutions to consider, such as the ones listed below.:
CRM with AI capabilities: CRM platforms that leverage AI to optimize sales processes and provide predictive insights can automate data entry, provide lead scoring, offer personalized recommendations, and optimize sales workflows. Examples include: Salesforce Einstein, Microsoft Dynamics 365 AI for Sales, and HubSpot Sales Hub.
Sales Engagement Platforms: Sales engagement platforms that leverage AI to improve communication and engagement with prospects and customers, and offer features such as email tracking, cadence automation, call coaching, and AI-powered analytics to optimize outreach efforts. Examples of sales technology used include: Outreach, SalesLoft, and Groove.
Conversation Intelligence: Leveraging AI to analyze sales calls and meetings to helps automatically provide insights into sales conversations, identify successful sales tactics, and offer coaching opportunities based on data-driven sentiment analysis. Top picks include: Gong.io and Chorus.ai.
Lead Generation: These tools help sales teams identify and target potential leads more effectively using AI algorithms to analyze data and provide accurate prospecting information. Examples include: LinkedIn Sales Navigator and DiscoverOrg.
Sales Analytics and Forecasting: These advanced tools help sales teams gain deeper insights into their pipeline, track performance metrics, and forecast sales outcomes through historical data analysis and predictive sales cycle forecasts. Clari, InsightSquared, and Tableau are top examples in this category.
Sales Chatbots: AI-powered chatbots that engage in real-time conversations with customers and assist with lead generation, customer support, and nurturing. These chatbots leverage natural language processing and machine learning to understand and respond to customer inquiries. Some examples include Drift, Intercom, and HubSpot Service Hub.
AI Sales OS: Alternatively, they find an AI-powered Sales Operating System like the one from Copy.ai to apply automation to all of their go-to-market sales functions.
AI Sales OS by Copy.ai offers workflows for the full sales process in one place— which are best for their needs:
Now, the sales team is ready to explore the potential of AI. They decide to start with a pilot program, implementing an AI sales tool in one specific use case. Rather than overhauling their entire process, they choose to focus on automating cold outreach using Copy.ai, allowing them to test how the AI tool performs in a controlled environment.
During the pilot phase, the team actively gathers feedback, assesses how well the AI tool integrates with their existing workflows, and makes any necessary adjustments. As they start seeing positive results from the initial weeks, they begin expanding the use of AI in other areas of the sales process, gradually enhancing efficiency across the board.
To ensure the new AI tools are used effectively, the team organizes comprehensive training sessions to the sales reps on how to use the new AI tools and incorporate them into their workflow.
The sales manager doesn’t just hand over the new tools — they invest in hands-on training sessions, resources, and documentation to ensure everyone understands and feels comfortable using the AI technology.
It’s a bit of a learning curve at first. Some team members are skeptical, while others are excited about the new possibilities. But as the weeks go by, the team starts to embrace the AI-powered tools and incorporate them into their workflows. Their efficiency improves, and they feel more empowered to focus on high-value tasks like building relationships with prospects.
With AI fully integrated into the sales team’s workflow, it’s time to set goals and metrics. What success looks like needs to be clearly defined.
The sales manager sets specific Key Performance Indicators (KPIs) to measure the impact and success of the AI implementation.
This could include metrics such as increased lead conversion rates, reduced response time, improved accuracy in forecasting, or enhanced customer satisfaction. The team regularly tracks and analyzes these metrics to gauge ROI and make data-driven decisions.
As they begin to see more leads convert, less time spent on manual tasks, and better forecasting accuracy, the team knows they are on the right track. These data-driven insights are key to refining their AI strategy moving forward.
Finally, the team creates a rollout roadmap to guide the phased implementation of AI in their sales team processes. They don’t rush — instead, they prioritize areas that will have the most immediate impact and gradually expand their AI usage across different processes.
The roadmap includes timelines for implementing new tools, training staff, and evaluating the impact of each AI solution. The sales manager ensures everyone is on board, communicates the plan to all stakeholders, and stays flexible, adjusting the timeline if necessary.
By following these best practices, they can implement AI across their sales team smoothly and maximize the benefits for their sales leaders and entire organization.
Remember to continuously monitor, evaluate, and optimize the use of AI to stay ahead in the competitive sales landscape.
While AI may not be able to convert a prospect on an hour-long call just yet, it can and does lighten the administrative load, automate the busywork, and set you up to deliver value in every sales call you make.
Are you ready to lead the revolution in sales excellence? Embrace the future of sales, where AI provides intelligent, data-driven solutions that enhance every step of your sales journey.
With AI Sales OS, your sales team can work smarter, not harder, unlocking new levels of productivity, insight, and success.
Embrace the future with AI Sales OS, where cutting-edge artificial intelligence empowers your sales team like never before.
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