Generative AI: How it Automates Data Entry and Provides Real Insights for Revenue Teams

Illustrator: Adan Augusto
how to automate data entry with ai

Manual data entry might once have been the cornerstone of CRM operations, but today, it has become a bottleneck that takes up too much of sales professionals’ time, hinders their productivity, and ultimately can impair their ability to better connect with prospects and close sales deals. 

However, accurate and timely input data remains an important part of sales and other revenue operations, since it provides key information about customers that can lead to better sales outcomes. 

So, how do businesses take manual data input out of the sales equation? 

Enter Generative AI and its capabilities to automate data entry and empower revenue teams with actionable customer insights. In this article, we’ll explore common problems that arise from manual data input, how AI automates the process, and how you can adopt it into your sales operations. 

Challenges of Manual Data Entry

Manual data entry presents significant challenges for businesses — it’s prone to human error, it’s an overwhelming task in bigger-scale organizations with significant data volumes, and it’s very time-consuming. According to Salesforce’s State of Sales report, sales reps spend nearly 10% of their time every week manually entering customer and sales information into systems

Before we dive into the strategies that can help overcome these challenges, let’s take a closer look at each of them. 

Human Error  

Manual data entry is prone to human error. Everyone is susceptible to making mistakes, which can include mistyping a phone number or email address, forgetting crucial information, or duplicating existing entries. 

We know that to err is human, and these kinds of mistakes, individually, are not a big deal. However, in a business environment, they can snowball into larger issues such as data inconsistency or even lower conversion rates. 

Finally, relying on manual data entry can create data silos, since information is not input correctly or timely across systems. 

Delays in Data Entry

Speaking of timely data entry, that’s not always the case when it’s done by hand. 

Consider everything that goes into it: customer data comes in from various touchpoints, such as email, chat transcriptions, and social media, to name just a few. Sales reps need to gather all this information, and then input it manually into a CRM. All while trying to pay as much attention to detail as possible to avoid mistakes and data inconsistencies. 

If you consider that this is not the only task they have in hand throughout their day, it’s no wonder manual data entry ends up getting delayed, which in turn leads to delays in updating customer records and generating insights. 

Overwhelmed Sales Representatives

The Salesforce State of Sales report shows that sales professionals spend only 28% of their time on actual selling-related tasks like prospecting and connecting with customers. 

So, what about the other 72%?

As mentioned above, almost 10% of that is spent manually inputting data into systems. On top of that, on a daily basis, sales reps have to complete an array of other low-value tasks that demand their attention, such as preparation and planning (9%) and other administrative tasks (8.8%.)

It’s no wonder, then, that sales professionals are often overwhelmed and can’t dedicate as much time as they would like to closing deals and driving the business forward. 

In terms of day-to-day operations, the first people impacted by this are, obviously, the sales reps. However, the problems manual data entry can cause go way beyond that, and include:

  • Hindered decision-making processes and low business agility;
  • Missed opportunities and lost revenue;
  • Reduced sales team's ability to respond swiftly to lead inquiries.

Connecting with customers at just the right time can make or break a deal, but it’s not always possible if sales representatives are otherwise busy.

Generative AI to the Automation Rescue

By now, it’s no surprise that generative AI can step in as a solution to manual data entry in a revenue operations context. It can be applied to automate low-value, high-cost tasks — which include data entry — freeing up your sales reps’ time to focus on more strategic initiatives, like closing deals. 

Typically, generative AI uses machine learning algorithms and natural language processing (NLP) to help automate data entry by:

  • Extracting data: thanks to NLP, AI systems can understand and interpret text-based customer information to then recognize patterns and extract data from various sources such as email, social media, and others. 
  • Transforming data: generative AI can turn information into structured data that’s suitable for entry into the CRM, whether by standardizing the data format and categories or ensuring consistency across the different types of data and data sources. 
  • Data validation: AI algorithms can validate data by cross-referencing it with existing data in the CRM and flagging inconsistencies, ensuring that data is accurately input. 
  • Automating repetitive tasks: certain tasks involved in data entry, such as updating contact information, logging sales rep/customer interactions, and categorizing leads, can be automated with generative AI. Thanks to its ability to learn from historical data, AI systems can streamline these tasks over time. 
  • CRM integration: certain generative AI solutions are designed to integrate with CRM systems, which allows for smooth data transfer. Additionally, the data input by AI can immediately become available to sales reps for action. 

Leveraging generative AI to automate data entry helps businesses address the challenges mentioned in the previous sections, eliminating manual data entry delays, reducing the risk of error and eliminating human error altogether, and ensuring data consistency and accuracy in your CRM. 

Not just that, but thanks to its ability to process vaster amounts of data in less time than any human agent could, generative AI helps businesses identify patterns and uncover insights that enable revenue teams to make smarter decisions and drive more sales. 

The benefits are clear, and revenue teams that are already using generative AI for data entry and processing can attest to how much it has impacted their day-to-day.

According to HubSpot’s The State of AI In Sales report, sales professionals have so far used AI mostly as a productivity assistant in daily tasks, with 14% using it for data analysis and reporting.

When it comes to that, 76% of sales professionals agree that AI can help organize and share data more effectively. It can track and collect customer data coming in from multiple sources, and consolidate all of it into a single source of truth — the CRM. 

In addition to automating data entry, AI also contributes to more data-driven decisions. 73% of sales professionals claim that AI has helped them pull insights from data they would otherwise not be able to find, with 65% saying that AI helps them understand prospects better. 

So how does all this take place?

Conversational AI

One of the ways businesses can implement generative AI to automate data entry is through conversational AI

AI-based chatbots can automate any routine tasks that involve data entry and processing, such as collecting data from various sources and customer touchpoints in real-time, and making this data instantly available to sales professionals by integrating with the CRM they use.

As it collects new data, conversational AI can also automatically update existing customer profiles, ensuring that sales representatives have access to up-to-date information they can resort to during meetings and other interactions with prospects. 

However, conversational AI’s ability goes beyond just collecting and storing data. It can also help sales representatives interpret that data, providing them with a more comprehensive overview of each individual prospect’s buying journey. This way, sales representatives can tailor their approach to new prospects and provide a better experience. 

Adopting Generative AI Into Your Revenue Operations

If, by now, you haven’t yet adopted generative AI into your revenue operations, I’m afraid you’re falling behind. 

According to HubSpot’s report, 69% of sales professionals state that by this year, most people will use some form of AI or automation to assist them in their jobs. Among many reasons for this, 78% of sales reps say that AI helps them spend more time on more critical aspects of selling. By taking over repetitive tasks — for instance, data entry — and automating them, AI frees up sales teams’ time to focus on selling, and even more so on the human side of it. 

With AI’s proven benefits in data entry and management, and sales peers claiming that it’s changing how they do business, what are you waiting for?

Generative AI application in revenue operations doesn’t have to be complicated, especially if you’re working with the right partner. 

With Landbot, you can leverage AI for different use cases in your sales operations:

  • AI FAQs Assistant: the AI FAQ Assistant can answer your prospects’ most commonly asked questions 24/7.
  • AI Sales Assistant: Landbot’s AI Sales Assistant answers prospects' questions, collects their data, qualifies them, and hands the qualified ones over to your sales reps.
  • AI Appointment Assistant: with the AI Appointment Assistant, your leads can book appointments at their convenience through a conversation. 

Regardless of the use case, each of these AI assistants collects valuable customer data during their interactions, enabling you to gain more insights into their behavior and preferences. 

That data is then input into your CRM or other storage system you might use thanks to Landbot’s native integrations — Salesforce, HubSpot, Airtable, and Google Spreadsheets. All automatically and instantly. 


As businesses navigate constantly evolving technologies and subsequent customer expectations, efficient data management remains a key aspect of revenue operations. 

By automating data entry, businesses can not only guarantee timely and accurate customer data entry into their systems, but they’re also able to uncover more customer insights and make more data-driven sales decisions. 

Ultimately, with generative AI as an ally, sales leaders can give sales representatives a solution to a time-consuming task that is prone to human error, which can keep them from reaching their goals, such as focusing on sales and closing deals.