Lead generation

Attracting potential clients is a crucial aspect of any business development strategy. However, traditional methods of lead generation can be labor-intensive, costly, and sometimes ineffective. A neural network with automatic selection of interlocutors can solve many of the problems that businesses face when it comes to finding clients and partners.

The AI algorithm allows for efficient and targeted lead generation by identifying potential customers based on specific criteria. The system can filter out irrelevant profiles and prioritize those who are most likely to become clients.

In addition, AI can analyze and evaluate the quality of leads based on their engagement with the company's content and their behavior. This allows companies to focus their efforts on those leads that are most likely to lead to sales, saving time and resources.

In particular, Eontribe's solution is designed to address a range of modern business pains, thereby increasing its effectiveness and reducing costs. In particular, the difficulties of modern companies engaged in lead generation can include:

• Incompetent, unprofessional lead generation specialists

One of the main problems when searching for and negotiating with potential clients is the use of unprofessional salespeople and negotiators who lack the necessary skills and knowledge for effective communication with potential customers. This can lead to unsatisfactory results and a waste of company resources. Thanks to the neural network and automatic selection of interlocutors, the system can automatically select potential leads for the company based on specified criteria. This reduces the need for a salesperson, as AI can handle the initial communication and provide the lead with the necessary information.

• High involvement of human resources in generating one lead

Finding quality leads can be a difficult and time-consuming process. The traditional approach involves searching for potential leads in various databases, social networks, and other sources. This can lead to an expansion of the staff, who need to sift through and find potential customers. With the help of a neural network and automatic selection of interlocutors, the system can simplify this process by automatically matching the company with potential leads that meet specified criteria. This reduces the time and effort required to find leads and increases the efficiency of the lead generation process.

• Low qualification of staff

The qualification of lead generators may be low, which leads to a low conversion rate. Thanks to the neural network and automatic selection of interlocutors, the system can analyze the responses of potential clients and determine their level of interest, payment ability, and relevance to the company's services. This allows the company to focus on those leads that are more likely to convert into clients, increasing the overall success rate of the lead generation process.

• Large volume of spam

Filtering out irrelevant messages can take a lot of time and be frustrating. Even teams with highly qualified search specialists are not immune to spending dozens of hours sorting through useless, advertising, and irrelevant proposals from suitable candidates. AI is capable of automatically filtering out spam. This reduces the amount of time and effort required to find qualified leads and ensures that the company's resources are not wasted.

• High employee costs

Hiring and training specialists can be expensive, and traditional lead generation methods often require a large sales or HR department to handle the process. Thanks to the neural network and automatic selection of interviewees, the system can automate much of the lead generation process, reducing the need for a large workforce. This can lead to significant cost savings for the company, allowing it to redirect resources to other areas of the business.

• Related to the above, slow development of the company

Inefficient lead generation processes can hinder the development and growth of the organization. By optimizing the lead generation process with the help of a neural network and automatic selection of interviewees, companies can increase their efficiency, reduce costs, and focus on developing other business areas. This can lead to long-term growth and high performance.

• Simple matching and search

The operation of a neural network on the Eontribe platform is often a two-way process. An example of this can be the job search process. On one hand, there is a worker who specifies their skills, occupation, experience, and other parameters. The job seeker can also configure the neural network to target companies with specific geographical location, industry, corporate culture, and so on.

On the other hand, there is a company that wants to hire an employee. In the Eontribe ecosystem, this company does not necessarily have to post a job description or make multiple posts on this topic in their profile. It is enough to specify the parameters of job seekers that best fit the vacant position.

When the queries match, the digital copy of the job seeker contacts the digital copy of the employer organization. A conversation may be conducted on behalf of both parties to clarify details and determine the priority and relevance of this result in the output of each participant (worker and employer). If the match is confirmed for both parties as suitable, they will receive a corresponding notification and be able to continue correspondence and schedule a meeting.

Thus, each side saves a lot of time. The job seeker only needs to create one resume on the platform instead of sending different data to different services in hopes of fitting the requests of companies. The employer avoids the need to hire a recruitment team, HR specialists, and related departments. This saves time and the company's budget. Also, it has a chance to find a truly suitable specialist, not just someone who tailors their resume to match the data in the job posting.

It is also worth noting the speed of artificial intelligence. No human resources department employee or candidate selection specialist can review the resume of a job seeker, filter out the most suitable candidates, and conduct a brief interview in a few milliseconds.

Both parties receive a shortlist of the most suitable matches without the need to spend weeks selecting the most suitable candidates.