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RPA Customer Onboarding: Top 12 Use Cases in 2024

Written by
Cem Dilmegani
Cem Dilmegani
Cem Dilmegani

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

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Customers appreciate when they don’t have to work hard to get what they want. According to Gartner research, “96% of customers with a high effort service interaction become more disloyal, compared to 9% [with] a low effort experience.1 Gartner describes a high-effort service interaction as one that involves:

  1. Channel switching – telling the customer to reach out in a different way, such as by emailing
  2. Repetition of information – repeating a piece of information to no avail
  3. Generic service – lack of personalization in the interaction
  4. Transfers – transferring the customer back and forth to different departments
  5. Repeat interaction – not resolving the issue and asking/forcing the customer to call back

Especially in customer onboarding, these issues lower customer satisfaction. Customer onboarding automation with robotic process automation (RPA) can improve potential clients’ first impressions of the business. In this article, we will explore the 12 use cases of RPA in customer onboarding automation.

1. Know your customer

KYC automation is integral to broader customer onboarding automation efforts. Before the customer has signed, RPA robots can conduct a preliminary risk assessment of the potential client to determine if they are the right fit for the company. For instance, RPA is used in insurance to apply decision-based rules to determine the risk premium of a new client based on their age, occupation, gender, etc.

If the data provided is inconclusive, RPA software can route the ticket to a human in the loop to enquire about secondary information.

2. Contract automation

Another use case of RPA in customer onboarding automation is automatic contract generation by:

  • Extracting the new customers’ information from scanned documents and files
  • Inputting them on ready-made contract templates
  • Sending it to their emails for e-signature

Oredoo, a telecommunication company, processes 5 million 2 new mobile contracts annually in Algeria alone. So they automated their onboarding processes. Now, bots powered by natural language processing extract customer data from their website and generate new contracts for them.

Explore contract automation in more detail.

3. Orientation

RPA can provide customers with orientation materials and different kinds of tutorials for:

  • Getting in touch with the company in case of an issue
  • Navigating the company’s website or application
  • Using the recommended best practices for optimized business effect

The benefit is lowered operational costs as human reps would spend their time on other things while bots are answering FAQs.

4. Cross-selling

RPA bots can save customers’ website journey data and feed it to ML algorithms for data-driven upselling and cross-selling. For instance, web trackers can record a user’s interaction with the company web page. Personalized suggestion engines then use the data for personalized cross-selling, upselling, and recommendation.

5. Updating CRM

Once the client has signed, their information should be logged into the CRM and other systems. RPA bots can automate the ETL and the data extraction process without human involvement. Use cases include updating info such as:

  • Customer’s name
  • Customer address
  • Bank account information, and more.

This frees human workers from manually having to update the CRM and the customer info whenever a new client is signed. The time saving from not having to do these repetitive back office tasks can lead to higher levels of employee engagement and satisfaction.

Learn more about CRM automation.

6. Real-life status updates

RPA robots can automatically communicate onboarding status to sales reps, marketing managers, and other key decision makers in the company.

The onboarding process’ duration varies from business to business. Reportedly, the onboarding for a B2B software company is about 90 days. By having visibility into the status of each new customer’s onboarding, the sales department can pinpoint bottlenecks to address. The result will be a quicker onboarding.

7. Real-time answers

RPA chatbots can answer new clients’ questions, and connect them with a live agent. By leveraging answers from the knowledge base, misinformation spread is minimized, issue is quickly resolved, and customer satisfaction is increased. In addition, workload on back office and front office departments, such as call centers, gets minimized.

Moreover, intelligent automation also powers chatbots to ask questions from customers to learn more about them. The entries would be recorded on the registration form to, later on, be used as a backdrop for the KYC (know your process) process.

8. Internal reporting

RPA used in reporting can save valuable time for sales reps and streamline and standardize the reporting process.

Since RPA robots need little to no customized integration, they can glue disparate systems together and create accurate customer reports for different departments for further analytics. These reports could include the following:

  • The number of new customers that have been signed
  • The number of customer service call requests
  • Financial info and more.

9. Analytics for process optimization

Bots generate event logs of their activities. This allows the company to have a precise knowledge of how long each subprocess of the customer onboarding process takes. This allows bottlenecks to be identified and resolved for maximum customer satisfaction.

10. Segmentation

Intelligent bots leveraging RPA can identify the segment that each customer falls under. This can further help the customer reps in knowing the kind attention that each customer should get. For instance, if a customer is currently on the company’s “basic” package of offerings, the focus should be to enhance and maintain their experience to convince them to upgrade.

11. Follow up emails

RPA robots can connect with other mapping solutions (i.e., customer mapping) to send non-intrusive and timely emails to customers during their onboarding process. For instance, if a customer is shown to have spent some time on the FAQ page of the website, RPA can send an email asking them if they’ve found what they were looking for.

RPA also helps proactively engage customers prior to them having to reach out, thus improving the customer experience.

12. Ticket follow-ups

RPA can automatically create tickets, track resolutions, and include this data in the customer file. Automated follow-ups help reduce the number of abandoned customer tickets and ensure front office satisfaction. Lastly, if the rep or the bot is unable to resolve the issue, an automatic message can be sent to the client, asking them to get in touch with the company representatives again.

Learn more about RPA in customer service.

For more on RPA and onboarding

If you want to learn more about the use cases of RPA, read:

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Cem Dilmegani
Principal Analyst

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Cem's hands-on enterprise software experience contributes to the insights that he generates. He oversees AIMultiple benchmarks in dynamic application security testing (DAST), data loss prevention (DLP), email marketing and web data collection. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

Sources: Traffic Analytics, Ranking & Audience, Similarweb.
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Science, Research and Innovation Performance of the EU, European Commission.
Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

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