Artificial intelligence

Ai is a fashionable word that has existed for decades, but recent advances in machine learning and voice recognition have made it applicable to more areas of society than ever, like sales teams.

Artificial intelligence in the sales process has been a great success for many companies. Also known as AI, it is a field of computer science and engineering that deals with the automation of the intelligent behavior of machines that has the potential to make those machines acquire intelligence and can solve problems in a more efficient, fast, scalable way. and without errors, when compared to human interventions.

Instead of spending a lot of time and effort prospecting, AI can do it automatically by scanning LinkedIn profiles or social media feeds. There are also tools that use natural language processing to read industry news articles for potential clients to find opportunities for outreach conversations with decision makers at these companies.

AI is thus once again becoming a buzzword in the business context, but this time recent advances in machine learning and speech recognition have made it applicable to areas such as customer management. (adaptive interface agent), as well as sales processes, which are currently benefiting the most from smart solutions (data collection and analysis).

In customer management, artificial intelligence is used primarily as an adaptive interface agent, helping to guide people through their journey from knowledge to purchase, without having human agents available 24 hours a day. This frees up humans for more complex interactions, while still providing help when needed. This creates better service by allowing AI to focus on one interaction rather than juggling dozens simultaneously. But with AI, it’s not just about productivity – it’s important for companies to balance automation with personalized interaction in order to maintain connections without sacrificing efficiency.

I. What is artificial intelligence?

Artificial intelligence is the theory and development of computer systems capable of performing tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI can be divided into three different types: general artificial intelligence (which is intelligent in many areas), restricted artificial intelligences (which perform specific functions such as face recognition or natural language processing), and social robotics (which creates robots for the company). Thanks to it, computers can now do things like recognize faces in photos with facial recognition software or drive cars autonomously thanks to artificial neural networks.

II. Benefits and risks associated with AI in sales processes

In the sales process, AI is often used for data collection and analysis in order to gain an advantage over competitors. This type of technology brings concrete benefits, such as increased productivity by using an intelligent system instead of humans when making decisions about the content that should be sent to customers. But AI also carries risks, such as the potential for biases to be introduced into decision-making if humans are not involved in specifying how algorithms should use data.

III. Examples of AI technology used today

To avoid biases being introduced into decisions, it is important that companies balance automation with personalized interaction to maintain connections without sacrificing efficiency for fear of introducing those human biases.

  1. Examples of preselection and qualification of accounts. It’s no secret that B2B buyers do their research and educate themselves before starting to interact with a supplier. In fact, according to a study by CSO Insights, more than 50% of buyers make purchasing decisions based on their own research before contacting a seller. If we don’t reach those buyers before they have made up their minds, you will most likely miss out on the opportunity to interact with them; worse, that budget is likely to be taken by competitors. That’s why having access to buyer intent data is so crucial – it enables us to join the conversation sooner with the right buyers.
  2. Segmentation. Targeting the right customers with the right message at the right time is one of the most efficient ways to optimize marketing campaigns and achieve a higher return on investment (ROI). And when a customer receives personalized content, there is not only a greater chance that they will buy the product, but also that they will develop loyalty to the business. As early as 2014, Forrester reported that more than 75% of sales and marketing professionals used advanced analytics and grouping techniques to personalize targeting. And 68% were already using machine learning algorithms for more personal orientation and interactions.

One of the key challenges marketing teams must solve is allocating their resources in a way that minimizes cost per acquisition ”(CPA) and increases return on investment. This is possible through segmentation, the process of dividing customers into different groups based on their behavior or characteristics. Customer segmentation can help reduce waste in marketing campaigns. By knowing which customers are similar to each other, you’ll be better positioned to target the right people with your campaigns.

  • A new approach to market research. Increasingly, companies are leveraging artificial intelligence for product development and design of the steps and stages of their journey. At PepsiCo, for example, various teams leverage artificial intelligence and data analytics to bring new products to life, gather information on potential product categories and flavors. This allows the R&D team to collect the kinds of information that consumers don’t report in focus groups and end up with the use of AI to analyze how those data-driven decisions unfolded.
  • Generation and targeting of audiences. Segmentation of specialized audiences through artificial intelligence technology uses proprietary high-intention customer data to create awareness. Thus, we can show the right ads to the ideal user at the most appropriate time so that that user can become the most loyal customer that drives a higher customer lifetime value.
  • Filtering and dialogue with buyers. AI customer recommendation system is now a super useful kind of material for multiple eCommerce industries around the world. It is a means used by developers to predict people’s intent or choices in advance. Generally, the algorithms of recommendation systems are based on the purchase history and page views made by customers.
  • Delivery of information at the best time. Decision-making from an AI perspective requires incorporating data throughout the entire customer journey into a single 360-degree customer view. The data comes from a wide variety of sources, which has implications for customer identity management, and covers a wide range of topics: a customer’s recent web visits, the emails they have received, or their last interaction with. a Sales Rep from the call center. Customer Data Platforms (CDPs) are sets of tools that can ingest and unite data that would not be as easily integrated into a traditional data warehouse and could result in a single customer having multiple identities. Once the organization has achieved this unique view of the customer, CDPs can calculate scores for different customer metrics, such as Customer Lifetime Value (CLV), based on business rules. NBA algorithms can be applied across channels to convert these calculated customer attributes into 1: 1 marketing.
  • Next Best Action in the customer journey. The “next best action” (Next Best Action or NBA) generally refers to predictive and prescriptive machine learning algorithms that help organizations find patterns in the way customers respond to different touchpoints and then determine which actions are more likely to convert. As customer behavior changes, your behavioral data feeds into the algorithm, which recalculates the likelihood of conversion for different touchpoint options. The NBA’s decision chooses the best channel to convey the best message and / or product at the best time.
  • Sales prediction. Imagine an alternate reality where your marketing efforts and expenses are realized only when your potential customer tends to make a purchase. The conversion rate would always be at a maximum, and advertising spend only takes place when the customer is likely to make a purchase. Having the data on when the product will be sold would give the customer the idea about the inventory that needs to be restocked. This would not only eliminate the large sum of unwanted costs, it would also make salespeople more efficient. This is much more useful in the industry that tends to sell concert tickets or provide transportation for people.
  • Personalization. The growing benefits of artificial intelligence in e-commerce have allowed e-commerce companies to increase their engagement rate, conversion rate, and decrease transaction time. So now you can send the right message at the right time because personalization has monitored the device and channels to create the customer view.
  • Identification of trends in those accounts most conducive to the organization. AI can make your search engine smarter. AI-powered search engines track your browsing patterns and search accordingly to help you find exactly what you’re looking for. With deep learning, search engines powered by artificial intelligence extract information from big data. They use the search term you enter and go deep into the conversation with the customer.

 IV. How to apply AI in sales processes?

AI is used today in many different fields, from healthcare to customer service. In the case of its application in sales processes, we must consider some previous aspects before its implementation. How will artificial intelligence affect all the aspects involved before implementing it in your organization? There are many considerations about this technology to take into account before deciding whether or not to implement it, such as the amount of data you have and the type of tasks you want to automate. The benefits of AI include increased productivity through automation and cost reduction measures, but there is also some risk associated with adopting this new system. Aspects such as the following must be taken into account:

  • You need to decide between general AI, restricted AI, or social robotics.
  • You must determine how to use the data collected by technology and human supervision.
  • It is necessary to evaluate the risks associated with the introduction of this type of technology in your organization, as well as the advantages that it entails.
  • Create a plan to monitor progress over time: How will you know if artificial intelligence is working? What are your expectations for increased productivity and reduced costs? Will there be trade-offs in other areas such as the quality and effectiveness of the business process or customer service? Will information be lost or will we be able to capture the attention of our buyer?
  • General AI may not be suitable for all companies because it requires high-cost computational resources and extensive training; however, it has many benefits, such as the ability to process information on multiple levels at the same time and learn from past mistakes.
  • Restricted AI can automate certain functions, such as natural language processing or facial recognition; however, the downside is that it requires a lot of data for the algorithms to work properly.
  • Evaluate the risks associated with the introduction of this type of technology in your organization, as well as the benefits associated with it
  • The introduction of artificial intelligence implies a strategic plan over time, as well as implications such as measuring success or decreasing the quality of customer service.
  • Companies should not focus solely on reducing costs; they must also consider how the introduction of this technology will affect their organization in all respects.

V. What are the risks? The benefits?

The introduction of artificial intelligence in sales processes must imply a strategic plan to measure success over time, as well as take into account the trade-offs associated with increased productivity and not focus solely on reducing costs. For example, does automation lead to lower levels of customer service quality due to decreased human interaction and engagement? Are there other areas that may suffer (such as company culture) when AI is introduced to this field without proper planning?

Although the introduction of AI has been associated with the loss of jobs in other industries, there are no definitive conclusions on this fact to the extent that other types of jobs related to artificial intelligence, machine learning, are generated. advanced computing, autonomous driving or Data Science, to give a few examples. It is true, however, that it requires an effort to retrain workers to work alongside smart systems and take advantage of its benefits, such as increased productivity thanks to automation, rather than focusing solely on cost reduction. .

VI. Conclusion on artificial intelligence in sales processes

AI has many advantages when applied to specific areas such as customer service and marketing, as companies have found a way to integrate it successfully without negative effects on the productivity levels of large organizations, due to the automation of tasks by computers that perform those functions more efficiently than humans could do on their own (for example, using Amazon from the company Alexa).

Although the introduction of AI has been associated with job losses in other industries, it is not a definite fact that this will occur. It may be possible to retrain workers so that they can work alongside smart systems and take advantage of their benefits, such as increased productivity through automation, rather than focusing solely on reducing costs.

At first glance, artificial intelligence may seem like an ideal solution for companies looking to cut costs, but there are many things to consider before implementing this technology in your organization: How much data do you have? Is AI appropriate for what you are trying to automate? How does human supervision fit into all of this?

Artificial Intelligence sales and customer management

AI is a new technology with extraordinary potential that can really change the practices of customer experience management and companies. It is important that companies ensure that they use it responsibly due to the responsibility that its use implies. The key is to balance automation with personalized interaction so you don’t lose efficiency and maintain connections without sacrificing productivity.

It’s important for companies to balance automation with personalized interaction to maintain connections without sacrificing efficiency for fear of introducing those human biases – artificial intelligence can have many benefits, such as increased productivity due to smart systems instead of let humans make the decisions about what content to send; However, it also carries risks that include the potential for biases to be introduced into decision-making if humans are not involved in specifying how data from algorithms should be used. In any case, its potential is relevant to the commercial process and we encourage you to try to test some parts of the commercial process with the incorporation of technologies based on artificial intelligence.

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