AI tools for marketing, sales and HR
Research Summary
May 2024
This report by SBS Consulting analyses the use of neural networks in various business processes. It analyses examples of successful implementation of AI technologies in marketing, customer service and HR, as well as their impact on efficiency and productivity. The report presents specific cases and assesses the potential for increasing efficiency through the use of neural network solutions.

Marketing

Use cases of neural networks:

  1. WriteMail.ai

    Process: Generating text content for marketing purposes

    Scope: Writing template texts for social networks and mailing lists, event announcements, standard posts, internal and external marketing mailings

    Estimated efficiency gains: 30%

  2. ChatGPT

    Process: Paragraph-by-paragraph text generation for websites, keyword-based writing of long-form articles/p>

    Scope: Content generation for websites, text improvement

    Estimated efficiency gains: 40%

  3. Deepl

    Process: Synchronising the English version of the website, improving texts

    Scope: Checking English texts, creating engaging images

    Estimated efficiency gains: 40%

  4. Midjourney

    Process: Generating background images for posts and corporate presentations

    Scope: Icon and image creation

    Estimated efficiency gains: 30%

  5. Namecheap and Namelix

    Process: Generating ideas for naming and logos

    Scope: Creation of corporate identity, including business cards and brand books

    Estimated efficiency gains: 30-40%

Impact on marketing:

  • Improved quality of texts and images
  • Reduced cost of content creation
  • Increased customer engagement through high-quality and personalised content

Customer service and sales

Use cases of neural networks:

  1. EBI.AI

    Process: Automating responses to customer enquiries

    Scope: Responses to simple queries, with complex cases left to the operators

    Estimated efficiency gains: 80%

  2. DigitalGenius

    Process: Generating templates for email responses

    Scope: Incoming message processing

    Estimated efficiency gains: 20%

  3. LivePerson and Botmother

    Process: Automating customer support via chat

    Scope: SIM card activation, account management, call handling

    Estimated efficiency gains: 34-40%

  4. Conversational AI (neuro.net)

    Process: Processing orders without operator involvement

    Scope: Sale products and services, complaints handling

    Estimated efficiency gains: 34%

  5. Haptik

    Process: Automating calls to customers

    Scope: Provision of information, sale of services

    Estimated efficiency gains: 60%

Impact on customer service and sales:

  • Reduced customer support costs by 20-40%
  • Increased productivity of customer service departments by 30-50%
  • Increased number of customers and potential sales by 50%

HR

Use cases of neural networks:

  1. AI4HR and ChatGPT

    Process: Generating job descriptions and postings

    Scope: Job descriptions, job postings, interview recording, meeting transcription

    Estimated efficiency gains: 50%

  2. Chatbots

    Process: Interviewing and evaluating candidates

    Scope: Testing, interviewing

    Estimated efficiency gains: 25%

  3. Nanonets and Gamma

    Process: Processing of single-type documents, designing presentations

    Scope: Training and seminar preparation, test and quiz design

    Estimated efficiency gains: 20-25%

  4. Quizgecko

    Process: Creating tests on a given topic

    Increased productivity of the HR department

    Improved quality of candidate selection and adaptation

Impact on HR:

  • Reduced recruitment and training costs
  • Increased productivity of the HR department
  • Improved quality of candidate selection and adaptation

Conclusion

Implementing neural networks in marketing, customer service and HR can significantly increase efficiency and reduce the cost of routine tasks. Neural networks help improve content quality, automate customer service and optimise HR processes. The examples of successful application of AI technologies show that companies implementing such solutions gain competitive advantages and improve operational performance.

The authors of the study
  • Vladimir
  • SAMOKHVALOV
  • Managing partner
Anastasia Mikheeva
Project Manager
Research Team
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