AI adoption flounders in CRM

Despite being touted as the future of customer relationship software, a recent study by Freshworks – a customer engagement company – revealed that only 12 percent of CRM users actually utilise an artificial intelligence (AI) tool. The study also found that 97 percent of CRM users think AI is too expensive, with 89 percent suggesting …

by | December 19, 2019 | bobsguide

Despite being touted as the future of customer relationship software, a recent study by Freshworks – a customer engagement company – revealed that only 12 percent of CRM users actually utilise an artificial intelligence (AI) tool.

The study also found that 97 percent of CRM users think AI is too expensive, with 89 percent suggesting it lacks utility.

"Research reveals hype around AI is falling on deaf ears because it fails to provide real value — more like artificial impact than intelligence," according to a Freshworks press release.

Amidst these findings, AI and machine learning have seen increased adoption in the client management software space over the past year. In March, researchers at Gartner predicted that 15 percent of all customer service interactions globally would be handled by AI, a 400 percent increase from 2017. Statista reports that by 2020, AI will generate an additional $105bn in revenue in CRM activities in the United States.

2020 is set to be a breakout year for CRM, with the Customer Relationship Management Software Global Market Report 2020 reporting that the global CRM market is expected to grow at a CAGR of 9.4 percent through 2022, with an expected value of $36.53bn.

Alongside a large dissatisfaction with AI, the Freshworks survey also revealed that 75 percent of CRM users are still interested in AI and would like to get more from it.

Where can AI be used?

AI, machine learning and deep learning have disrupted all industries. Within CRM, AI has seen widespread implementation through voice functionalities, with voice assistants being used to extract information from customer data. Salesforce’s Einstein project is an example. Zoho offers a similar product called Zia, which offers complex analytics through a chat function.

However, algorithmic personalisation is often limited to customer facing services, which neglects the behind-the-scenes functions that CRM could improve with.

According to a McKinsey study from June, fewer than 10 percent of companies surveyed currently deployed personalisation beyond digital channels in a systematic way. Machine learning in CRM is used to analyse customer data and discover behavioural patterns which would provide for greater personalisation, or deep personalisation.

A focus on personalisation is necessary as customer focus becomes key across financial services. A study done by Vision Critical predicts that customer experience will overtake price and product as the key brand differentiator by 2020. Accenture reports that a customer is 75 percent more likely to buy from a retailer if they are offered relevant recommendations and their purchase history is remembered.

The advent of AI in client management has led to speedy innovation within deep personalisation and increased customer engagement. Yet 56 percent of CRM customers were most dissatisfied with software promising functions and not delivering on them, according to a report by SoftwareReviews dated November 21. The technology may be present, but its efficiency remains uncertain.

Increased pressure on data and consent management

While the past year has revealed gaps in AI’s CRM reach, its role in efficient data governance remains essential. In recent years, the conversation around data has shifted from the old “data is the new oil” adage towards its management, with a focus on distinguishing between good and bad data. Poor management of customer data can lead to breaches, and client management software is particularly vulnerable as it is often used to manage a company’s data.

Within CRM, master data management (MDM) is one way that firms can collate a unified customer profile to handle their data. According to MDM provider Stibo Systems, CRM data can be incomplete or inaccurate due to several reasons: missing or incorrect data entries, or the presence of out-of-date data, for example.

Proper data management can help firms reach compliance in areas like Europe’s General Data Protection Regulation (GDPR), anti-money laundering (AML), and know-your-customer (KYC) initiatives. Since 2016, GDPR has created more opportunities for CRM in Europe, as software can assist in managing consumer data. According to CRM provider Wizard-Systems, CRM that does more than just collect personal data is vital to maintaining GDPR compliance.

On November 26, a group of US senators put forward a data protection bill similar to GDPR, the Consumer Online Privacy Rights Act (COPRA). The onset of greater regulation may lead to more client management use cases. Companies such as SuperOffice and Zoho currently manage customer consent to data usage, and revoke data that is not needed to ensure compliance.

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