The amount of data companies have on customers and the number of channels customers are using to interact with businesses have grown significantly in the past decade. Artificial intelligence may hold great promise in optimizing customer and client interactions.
The five largest Customer Relationship Management (CRM) vendors by market share in 2015 were Salesforce, Oracle, SAP, Adobe Systems, and Microsoft. These five companies make up almost half of the entire CRM market. All of them have been investing in their internal development of machine learning and AI, while also buying AI startups.
We will explore the AI applications of each of these five CRM leaders, helping business readers to understand:
This post will focus on is Salesforce. They are by far the dominant player in this sector with more market share than their top four competitors combined. They have been aggressively investing in AI to maintain their position and are the benchmark by which most other companies are being judged by possible clients.
Salesforce wants corporate clients to be convinced that AI is this the future of CRM. An IDC White Paper, sponsored by Salesforce, projects that the use of AI in CRM will boost global business revenue by $1.1 trillion from 2017-2021. They claim that it could result in 800,000 net new jobs.
Based on corporate data and their surveys, IDC believes this use of AI will grow dramatically in the next few years. A survey conducted by IDC found that 28% of all respondents say their organizations have already started using AI and an additional 41% plan to adopt AI in the next two years. IDC concluded that worldwide spending on cognitive/AI systems was only $8 billion in 2016 but believes that this spending could reach $46 billion by 2020.
It is probably in Salesforce’s interest to heavily emphasize the prevalence of AI in CRM, as they are the largest firm in the space, and the one most likely to invest heavily in CRM AI applications. For this reason we should take this report with a grain of salt. Whether or not you believe IDC’s projections, CRM services is a highly competitive and growing business sector.
Over the past few years, Salesforce has been aggressively developing AI services in-house and acquiring many AI companies. They have also signed major deals with other companies focused on AI.
According to CB Insights, Salesforce acquired four AI startups (Tempo, MinHash, PredictionIO, and MetaMind) during 2015 and 2016 to add their technology to their applications.
This focus on AI allowed Salesforce to introduce their AI tool, Einstein, in late 2016. Their goal is to simplify the use of AI for their clients, and make AI capabilities accessible to clients without a robust technical AI skill set. This emphasis on “accessibility” is a common value proposition for nearly all B2B AI applications, in CRM or otherwise – and time will tell if Salesforce can indeed make the tools accessible to less technical users.
Salesforces offers a broad range of uses for Einstein, including account insights, lead prioritization, automated data entry, ad personalization, insights into social media conversations, product recommendations, image classification, and more.
Black Diamond, a Utah-based outdoor equipment company, claims that it initially used to manually upload on-site product recommendations for its customers, which ate up their time. These manual recommendations were not personalized for the customer, meaning that it most likely did not recommend related or relevant products that the customer was most likely to buy.
Black Diamond also claims in its case study that after integrating its system with Einstein’s recommendation engine, which uses customers’ historic data, purchase behavior, and affinities to offer relevant recommendations through machine learning, it was able to increase conversions by 9.6 percent and drive a 15.5 percent increase in revenue per visitor. However, it is not clear in what time period (in days or months) they supposedly achieved these results.
They also claim Einstein Activity Capture was able to eliminate an hour a day of manual data entry for sales representatives at Silverline.
While the market price and demand for the CRM AI technology are currently high, Salesforce CEO Marc Benioff no longer sees major acquisitions as likely in the short term. Instead, he is working on improving their offering via partnerships. Their most high profile AI partnership is with IBM.
In March, Salesforce announced it was teaming up with IBM to integrate Watson’s data and tools into their CRM system, giving their clients access to Watson’s existing information sources and its ability to analyze their data. For example, integrating IBM weather predictions into their market strategies. Just one small example of how this partnership works is through the use weather forecasting, which IBM has heavily invested in become a world leader in. With real time access to Watson’s weather data, companies using Salesforce can directly warn their customers who might be negatively impacted by changing weather conditions.
For example, Watson might determine it is about to hail in Houston. Car insurance companies can then use Salesforce to quickly alert all their customers in the area about to be hit to take precautions.
Salesforce is also working to add new capabilities to Einstein. Two functions currently in beta are Einstein Intent and Einstein Sentiment. They use natural language processing to classify whether the text of a message is emotionally positive or negative and determine what the intent of the message is, respectively.
For example, a company could put to use Einstein Sentiment to classify the tone of their inbound customer emails and accordingly identify positive brand evangelists and escalate dissatisfied customer responses into service cases. Einstein Intent, on the other hand, can be used to augment Einstein Sentiment. It could classify each negative response and identify the source of customer dissatisfaction, like lost shipments and returned orders.
Another function in pilot is Einstein Object Detection. It is designed not only to detect and classify objects but also to identify different objects in an image and their location. Like the below video demonstrates, a company could use a picture of a shelf to quickly know how much inventory is on display or customer could take a picture of something they want and the program could tell them where to buy it.
Salesforce’s documentation page for Einstein Vision states that this application can be used within CRM to help customers find products, to help customer service agents identify a product related to a customer complaint, and more. We were unable to find any current use-cases of this technology with Salesforce’s customers.
The five largest Customer Relationship Management (CRM) vendors by market share in 2015 were Salesforce, Oracle, SAP, Adobe Systems, and Microsoft. These five companies make up almost half of the entire CRM market. All of them have been investing in their internal development of machine learning and AI, while also buying AI startups.
We will explore the AI applications of each of these five CRM leaders, helping business readers to understand:
- AI capabilities are currently available for each of the five CRM giants
- Tangible results have been yielded by today’s AI applications in CRM
- Upcoming AI applications are being developed and may be available soon
This post will focus on is Salesforce. They are by far the dominant player in this sector with more market share than their top four competitors combined. They have been aggressively investing in AI to maintain their position and are the benchmark by which most other companies are being judged by possible clients.
Salesforce wants corporate clients to be convinced that AI is this the future of CRM. An IDC White Paper, sponsored by Salesforce, projects that the use of AI in CRM will boost global business revenue by $1.1 trillion from 2017-2021. They claim that it could result in 800,000 net new jobs.
Based on corporate data and their surveys, IDC believes this use of AI will grow dramatically in the next few years. A survey conducted by IDC found that 28% of all respondents say their organizations have already started using AI and an additional 41% plan to adopt AI in the next two years. IDC concluded that worldwide spending on cognitive/AI systems was only $8 billion in 2016 but believes that this spending could reach $46 billion by 2020.
It is probably in Salesforce’s interest to heavily emphasize the prevalence of AI in CRM, as they are the largest firm in the space, and the one most likely to invest heavily in CRM AI applications. For this reason we should take this report with a grain of salt. Whether or not you believe IDC’s projections, CRM services is a highly competitive and growing business sector.
Over the past few years, Salesforce has been aggressively developing AI services in-house and acquiring many AI companies. They have also signed major deals with other companies focused on AI.
According to CB Insights, Salesforce acquired four AI startups (Tempo, MinHash, PredictionIO, and MetaMind) during 2015 and 2016 to add their technology to their applications.
- Tempo – An AI powered smart calendar app that shows you the information you need before a meeting, which Salesforce has since shut down.
- MinHash – An AI that looks for marketing trends, which Salesforce has since shut down.
- PredictionIO – An open source machine learning company, which Salesforce acquired for their technology and donated the open source addition to the Apache Software Foundation
- MetaMind – A deep learning company that specialized in technology, which Salesforce has since shut down.
This focus on AI allowed Salesforce to introduce their AI tool, Einstein, in late 2016. Their goal is to simplify the use of AI for their clients, and make AI capabilities accessible to clients without a robust technical AI skill set. This emphasis on “accessibility” is a common value proposition for nearly all B2B AI applications, in CRM or otherwise – and time will tell if Salesforce can indeed make the tools accessible to less technical users.
Salesforces offers a broad range of uses for Einstein, including account insights, lead prioritization, automated data entry, ad personalization, insights into social media conversations, product recommendations, image classification, and more.
Black Diamond, a Utah-based outdoor equipment company, claims that it initially used to manually upload on-site product recommendations for its customers, which ate up their time. These manual recommendations were not personalized for the customer, meaning that it most likely did not recommend related or relevant products that the customer was most likely to buy.
Black Diamond also claims in its case study that after integrating its system with Einstein’s recommendation engine, which uses customers’ historic data, purchase behavior, and affinities to offer relevant recommendations through machine learning, it was able to increase conversions by 9.6 percent and drive a 15.5 percent increase in revenue per visitor. However, it is not clear in what time period (in days or months) they supposedly achieved these results.
They also claim Einstein Activity Capture was able to eliminate an hour a day of manual data entry for sales representatives at Silverline.
While the market price and demand for the CRM AI technology are currently high, Salesforce CEO Marc Benioff no longer sees major acquisitions as likely in the short term. Instead, he is working on improving their offering via partnerships. Their most high profile AI partnership is with IBM.
In March, Salesforce announced it was teaming up with IBM to integrate Watson’s data and tools into their CRM system, giving their clients access to Watson’s existing information sources and its ability to analyze their data. For example, integrating IBM weather predictions into their market strategies. Just one small example of how this partnership works is through the use weather forecasting, which IBM has heavily invested in become a world leader in. With real time access to Watson’s weather data, companies using Salesforce can directly warn their customers who might be negatively impacted by changing weather conditions.
For example, Watson might determine it is about to hail in Houston. Car insurance companies can then use Salesforce to quickly alert all their customers in the area about to be hit to take precautions.
Salesforce is also working to add new capabilities to Einstein. Two functions currently in beta are Einstein Intent and Einstein Sentiment. They use natural language processing to classify whether the text of a message is emotionally positive or negative and determine what the intent of the message is, respectively.
For example, a company could put to use Einstein Sentiment to classify the tone of their inbound customer emails and accordingly identify positive brand evangelists and escalate dissatisfied customer responses into service cases. Einstein Intent, on the other hand, can be used to augment Einstein Sentiment. It could classify each negative response and identify the source of customer dissatisfaction, like lost shipments and returned orders.
Another function in pilot is Einstein Object Detection. It is designed not only to detect and classify objects but also to identify different objects in an image and their location. Like the below video demonstrates, a company could use a picture of a shelf to quickly know how much inventory is on display or customer could take a picture of something they want and the program could tell them where to buy it.
Salesforce’s documentation page for Einstein Vision states that this application can be used within CRM to help customers find products, to help customer service agents identify a product related to a customer complaint, and more. We were unable to find any current use-cases of this technology with Salesforce’s customers.
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