Guide: What new opportunities will this wave of AI bring to CRM companies?
ChatGPT has only been born for more than 100 days, but it has already had a huge impact on many industries.
The same is true for the front-line battlefields where enterprises face the market-sales, marketing, customer service and other fields. The upsurge of artificial intelligence technology represented by ChatGPT is changing the traditional marketing and sales operation mode, and has become a key force for enterprises to reshape their competitiveness.
"Intelligence will become the next hot spot in many industries. Surrounding ChatGPT and other generative AI technologies, SalesEasy has co-created many innovative attempts with some customers. For example, in the past, after sales visits to customers, it took a lot of time to sort out the visit records. Now AI can automatically generate very high-quality customer demand extraction and sorting based on customer communication records."
When CRM meets ChatGPT, there is actually a bigger topic behind it: in an era full of uncertainties, how can enterprises use data intelligence to achieve refined operations, empower front-line employees, and continuously "foresee" the next business opportunity? What new opportunities will this wave of AI technology bring to CRM companies?
Recently, Luo Yi, vice president of Sales Easy Technology, shared his views and insights to "Intelligent Evolution".
Intelligence has become the rigid demand of CRM customers
The generative AI technology represented by ChatGPT is becoming a key milestone in the application of data intelligence in enterprises. In the field of CRM, the demand of enterprise customers for data intelligence is increasing day by day.
In fact, data intelligence in the CRM space is not a new topic. In the core links of CRM such as marketing, sales, and service, how to mine data value, provide enterprises with better decisions, and ultimately improve customer satisfaction has always been the core value of CRM.
Luo Yi believes that intelligence must first solve the problem of data, and the quality, quantity and dimension of data are the key to the realization of the degree of intelligence. At present, there are still many enterprises in the process of digital transformation, which are still at the stage of not solving data collection and governance, which will directly affect the actual implementation of data intelligence in the next step.
Luo Yi believes that if we look at the development process of CRM itself, the intelligent capabilities in it can be divided into the following three development stages.
The intelligence 1.0 stage is represented by the continuously upgraded BI function. Based on the data collection, governance and analysis of the enterprise in key links such as marketing, sales, and service, CRM uses BI tools to complete preliminary data analysis and insights. At this stage, "Everyone BI" was once a differentiated advantage of SalesEase, aiming to lower the threshold of BI analysis tools, so that BI is no longer limited to specific managers, but becomes the data analysis of every front-line business personnel tool.
In the intelligence 1.0 stage, limited by data quality and intelligence capabilities, enterprises can gain limited insight from data, and it belongs to post-event analysis, which cannot meet more personalized and predictable needs.
The intelligence 2.0 stage is represented by personalized recommendations based on user portraits. With the popularization of new retail scenarios, with the help of digital tools, the scope and frequency of contacts between enterprises and consumers have been greatly improved, and the accumulation of massive customer data has become the basis for more accurate user portraits and personalized recommendations for "thousands of people and faces" .
In the stage of intelligence 2.0, enterprises have initially used some artificial intelligence technologies to gain deeper insight into customer needs. However, intelligent scenarios are still limited, and there is still a lot of room for development in the combination of intelligent technology and business scenarios.
In the intelligence 3.0 stage, more inclusive artificial intelligence and machine learning will reshape the intelligent experience in the CRM field. The generative AI technology and large models represented by ChatGPT have accelerated this process. In the future, the application scenarios of artificial intelligence in the field of CRM are more than people imagined, including but not limited to business opportunities, potential customer mining, sales forecasting, intelligent customer service, digital employees and so on.
"A typical scenario is the scoring of sales leads in the marketing process. In the past, scoring was often based on a set of manually set weight rules formed by expert experience. Now the large model lowers the threshold for AI model development, and machine learning can be based on customer historical data. And specific scenarios, train a more accurate scoring system, and seamlessly connect with the existing CRM system and tool platform." Luo Yi said.
Use AI to empower front-line employees, the starting point of intelligent CRM
It can be seen that the continuous evolution of intelligent capabilities in CRM is inseparable from a thread that runs through, that is, the core needs of customers.
" Enterprise customers mainly have two major requirements in terms of intelligence: one is the perspective of management and operation, not only to reduce costs and increase efficiency, but more importantly, to improve the dimension of refined operations. Through data-driven value insights, Provide support for key decision-making of enterprise operations. The other is to empower front-line business personnel, including marketing personnel, sales personnel, customer service personnel, etc., so that AI technology can truly generate valuable increments for their work.” Luo Yi express.
The refined operation of an enterprise is often based on empowering front-line employees. The two data intelligence products "Smart Customer Acquisition" and "Neo Suggest" launched by SalesEasy in 2022 are typical examples of using AI technology to empower front-line sales staff.
In the past, salespeople in the to B field searched for potential customers, usually using the contracted benchmark customers as a reference, and searched for other companies with similar business scenarios and needs on the third-party data platform.
This "Look-Like" model is also the underlying logic of SalesEasy's "Smart Customer Acquisition" products. "Smart Customer Acquisition" allows sales staff to directly search for 100+ dimensions of similar customer information in the SalesEasy CRM system by dismantling and refining the characteristic portraits of winning customers.
In the past, sales were not clear about whether the potential customers acquired in batches were already in the enterprise library, whether other colleagues of the same lead were following up, etc. Now, in SalesEasy CRM, sales staff can convert potential customers obtained by "smart customer acquisition" into leads with one click, and automatically screen out unqualified targets. At present, "Smart Customer Acquisition" has been implemented in hundreds of corporate customers.
"The most typical application scenarios of 'smart customer acquisition' are those whose target customers have long-tail characteristics and need to expand the market by region." Luo Yi introduced.
"Neo Suggest" (Neo Suggest) can be regarded as a sales champion replication tool.
In the past, sales skills were a very personal skill that varied from person to person, and the experience of gold medal sales was difficult to be imitated and replicated by other sales. With the help of AI technology, to discover which of the experience of gold medal sales can be standardized and precipitated, this is Neo Suggest.
Scene and real-time are the advantages of Neo Suggest. By learning customer historical data and intelligently judging the current stage of business opportunity promotion, Neo Suggest can provide personalized recommendations for the next action of the salesperson based on the context of the current communication between sales and customers.
For example, after confirming the customer's purchasing intention, Neo Suggest will suggest that the sales staff conduct one-on-one visits with key decision makers. When the project advances to the demand confirmation stage and needs to be further improved, Neo Suggest will call out a list of 3 solution experts who can provide relevant support, and evaluate the most recommended solution expert. When it comes to quotation, Neo Suggest will automatically select a suitable quotation template from the library, and automatically fill in the product, price and other business opportunity information, and the salesman only needs to confirm the details and send it to the customer with one click.
Compared with traditional intelligent systems based on artificial experience and fixed rules, "Smart Customer Acquisition" and Neo Suggest are both developed based on deep learning algorithms. "Smart Customer Acquisition" is trained from customer historical data and other multi-dimensional data, which can dig out potential business opportunities from a richer dimension. Neo Suggest's semantic understanding ability can intelligently provide real-time sales strategy suggestions based on the communication context.
" Our AI algorithm is based on the dimension of whether it can solve the actual business pain points of customers, and the dimension of implementation. " Luo Yi said.
How can CRM companies embrace the new wave of AI?
In the past few years, the integration of AI technology and the CRM field has led to the emergence of many star startups in the industry that have achieved breakthroughs in single-point scenarios through AI technology. For example, gong.io, which provides sales intelligence analysis and the next best deal strategy, and domestic benchmarking company Megaview, Clari, which provides AI predictive models and intelligent data analysis, and Zoominfo, which provides massive business contact information, etc. Over the past few years, these companies have been sought after by capital.
Today, what new opportunities will the AIGC technology wave led by ChatGPT bring to CRM companies?
An obvious trend is that Chinese and foreign CRM companies are actively embracing new technologies and trying to integrate AIGC technology into their own products and business scenarios.
In March of this year, Salesforce, the world's largest CRM vendor, launched a generative AI tool, Einstein GPT, for generating personalized sales promotions, marketing content, and codes. For its instant office communication software Slack, Salesforce also released a ChatGPT application, which mainly provides new functions such as summary of conversation points, research tools and writing assistance.
Regarding the two paths of single-point breakthrough and platform integration, Salesyi tends to take the latter path. "In terms of intelligence, it is difficult for a company to be the best in all segments. We hope to maintain the openness of the platform, integrate with players in these segments, and provide customers with a more valuable end-to-end end-to-end integration solution. ”
In addition, integrating intelligent capabilities into industry solutions is also one of the advantages of SalesEasy. Based on in-depth insight into the customer's industry and the open capabilities of PaaS, SalesEasy can implement intelligent solutions for specific industries and scenarios to meet customers' individual needs for intelligence.
Luo Yi said that for the latest wave of AI technology, including the current very popular large-scale models, SalesEasy has always maintained sufficient sensitivity, and is also actively exploring innovations in different scenarios with customers. For example, SalesEasy co-created with a leading central air-conditioning customer. With the help of AI technology, it can quickly extract core information such as the customer's house area, room type, core demand for air-conditioning, and selection tendency from a long customer communication record. Greatly improved the efficiency of sales staff.
Luo Yi believes that in the future, universal single-point scene AI applications will become increasingly popular. However, it is worth considering whether these technologies can help CRM companies build greater competitive advantages.
" For CRM companies, a more critical issue in applying AI technology is whether you have provided incremental value. Because for customers, single-point applications or technology can be used by anyone to solve problems. And our advantage lies in standing on the ground Dimension, constantly thinking about how to integrate AI technology into products, and bring real value to customers in specific business scenarios.”
The pictures in the text are from Photography Network
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This article is the original work of "Intelligent Evolution".