📚Real Selarti Case Studies
In this article, we look at real examples of how the service has been implemented and the business value it delivers.
An AI agent built in Selarti automates client communication, reduces operating costs, and scales operations. In every scenario, it handles similar tasks:
initiates conversations or responds to incoming inquiries;
identifies client needs and interests;
answers questions or handles objections;
collects the necessary information;
processes large volumes of conversations quickly;
transfers qualified leads to a sales manager or completes the process autonomously.
The business objective varies depending on the company. One company needs to book client consultations, another wants to win back customers, and a third aims to sell a service or product.
Below are case studies from clients who used Selarti across different industries. They will help you clearly understand which specific processes the AI agent is suited for, how the work is typically structured, and what results can be achieved.
Selling Power Supply Services
Business objective: identify potential clients in the database of procurement officers, chief power engineers, and business owners who are interested in power supply services, and pass them to a sales manager.
Communication type: outbound messages in Telegram.
AI role: sales manager.
How the AI worked:
identified the relevance of power supply challenges;
requested contact details for handover to a sales manager.
Results over three months of operation:
4,993 outbound dialogues;
2,834 responses (56.8%);
66 successful dialogues (2.2%);
$4.03 per sales-qualified lead;
three agents used.
Selling Saunas via Avito and WhatsApp
In this project, Selarti was used across two sequential sales stages.
Business objective: transfer a sales-ready client to the sales manager (two funnels involved).
Communication type: inbound requests on Avito, inbound and outbound messages in WhatsApp.
AI role: AI Sales Assistant, sauna barrel seller.
How the AI worked:
Stage one — Avito. After receiving an incoming message, the AI replied to the client's questions, qualified the prospect, and offered to schedule a call with the sales manager, requesting a contact number.
Stage two — WhatsApp. Once the phone number was obtained, the AI continued the conversation in WhatsApp. It clarified the request details and collected additional information so the sales manager could contact the client and close the deal.
Avito results:
806 inbound dialogues;
806 responses (100%);
284 successful dialogues (35.24%).
WhatsApp results:
548 dialogues;
502 responses (91.61%);
457 successful dialogues (91.03%);
$0.29 per hot lead.
The data was collected over three months of operation; two agents were used. During this period, Selarti guided customers across multiple communication channels and operated as part of a multi-stage sales funnel.
Customer Re-engagement for a Jewelry Retail Chain
Business objective: offer bonuses to customers who visited the store but didn't make a purchase, and motivate them to complete a purchase (large mass‑market jewelry chain).
Communication type: outbound to customers who had previously visited the store and not purchased.
AI role: customer Success Manager.
How the AI worked:
asked qualifying questions to identify interest;
offered suitable options or alternatives to encourage a purchase.
Results over three months of operation:
88,238 outbound dialogues;
4,597 responses (5.2%);
3,047 successful dialogues (66.3%);
$0.70 per successful dialogue;
one agent used.
This is a case where the AI was used for repeat sales and customer win-back.
Attracting Users to an Investment Platform
Business objective: get startup founders interested in registering on an investment platform.
Communication type: outbound messages in Telegram.
AI role: investment Consultant.
How the AI worked:
established contact and identified investment plans;
offered registration on the platform and presented its advantages;
collected contacts and client information for follow-up communication.
Results over one month of operation:
2,964 outbound dialogues;
926 responses (31.2%);
307 successful dialogues (33.2%);
$0.21 per qualified user;
two agents used.
Selling Medical Equipment
Business objective: bring private medical center representatives to a telephone consultation with a sales manager.
Communication type: outbound messages in Telegram.
AI role: sales manager.
How the AI worked:
identified whether equipment implementation was relevant;
collected contact information for transfer to the sales manager.
Results over one month of operation:
1,482 outbound dialogues;
748 responses (50.5%);
49 successful dialogues (6.6%);
$1.01 per consultation booking with a sales manager;
one agent used.
Attracting Users to the Platform
Business objective: attract clients to the platform who have an interest in automating business processes to improve employee performance, implement checks, reduce time, and increase employee efficiency. Target audience: business owners, directors, managers, COOs, quality control staff, HR specialists, marketers, and auditors.
Communication type: outbound messages in Telegram.
AI role: sales manager.
How the AI worked:
identified whether the need for business process automation existed;
scheduled a meeting.
Results over two months of operation:
4,301 outbound dialogues;
2,418 responses (56.2%);
70 successful dialogues (2.9%);
$3.12 per sales-qualified lead;
two agents used.
Increasing Registrations on the Platform
Business objective: engage the client with the convenience of using an digital wallet and guide them through to completing registration (English‑speaking market).
Communication type: outbound messages in Telegram.
AI role: client support manager.
How the AI worked: interacted with clients using the SPIN selling methodology.
Results over one month of operation:
1,467 outbound dialogues;
42 responses (2.9%);
15 successful dialogues (35.7%);
$1.81 per new user;
one agent used.
Attracting New Investors
Business objective: find potential clients from a cold database of private investors and pass interested leads to a sales manager.
Communication type: outbound messages in Telegram.
AI role: investment manager.
How the AI worked:
established contact and determined whether the person was an investor;
offered the opportunity to consider investing in the company and presented its advantages;
obtained contacts for follow-up and consultation.
Results over four months of operation:
5,879 outbound dialogues;
1,461 responses (24.9%);
318 successful dialogues (21.8%);
$1.12 per sales-qualified lead who agreed to schedule a meeting;
four agents used.
For more details on how to get started with Selarti, see the article.
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