In a strong business world, the relevance of a system that is able to maintain and also strengthen growth for any business’ client base in no way can be understated. Last year, the expenditures on CRM tool surged by 13% to reach more than $20 billion, stated IT research and advisory firm Gartner. It also went on to claim that the technology won’t be losing its appeal anytime soon. It is also expected that a CRM tool will continue to remain one of the most essential numerous digital initiatives of the future as well. Moreover, it will also continue to bag funding since digital business is important for firms to maintain its competitiveness.
Since companies invest a major portion of resources in CRM, it is essential that companies carry out a proper check on the software/tool for bringing out the best. There are numerous ways available for optimizing the CRM implementation, but it has been found that data analytics mainly provides exciting opportunities for introducing innovation in the sales process.
CRM data analytics can also help a business to push for a stronger sales process along with empowering the field personnel with smarter tools. It can be successfully carried out not by simply studying the available CRM data but by strengthening the data with extra details.
Initiate account planning
The basic premises for selling goods and services have been consistent, which means converting the opportunities into closed deals. But as the salesforce evolved and the potential for a national clientele, the sales process’ complexity exploded. Important sales activities now comprise of territory alignment, client segmentation and also account management at multi stages. It has been found that account planning gives the resources of the sales team to the clients and also the potential clients in an effective manner. It has been found that CRM analytics can prove helpful for the process by combining the previous sales activity data with the historical sales results and also other data influencers. When a sales team is asked to name the top 10 clients, the response should come quickly. But are they in a position to tell you about who the top 10 clients will be in the next quarter? But with the right sort of business intelligence, it becomes possible to answer questions easily. This way of information collection is an efficient way for companies to opt for segmentation of clients into prioritized groups.
Developing an improved sales call
CRM analytics has been useful for ensuring that a sales interaction is good. Creating an improved sales call is dependent on the right CRM details architecture. A CRM tool should not be able to keep track of the accounts and contacts but also the actual sales materials offered to those clients. There are numerous advantages of this setup. For example, the sales and marketing materials can be easily stored in the central location also consumed by the filed agents as and when required. Cloud based CRM tools make search of the email folders for the recent version of a PPT easy and quick. In this model, the usage and also the adoption rates of such materials can be easily kept track of. Few regulated industries can also automate the compliance procedures through the digital consent pacts when a client checks out certain content.
In regard to the consistent improvement, the feedback for the sales presentation materials can be collected from the client as part of the sales call. This feedback can be found in the CRM repository to bring improvement in the future. It has been found that the smarter calls have been developed by offering the client with the appropriate cross selling opportunities. It has been found that data analytics play an important role in deciding the cross sell chances. A company with enough order history and also client dimension data, models can be developed that will offer a suggestion list of extra products bought by the similar clients. But one of the most essential factors from the analytics side is for associating both the sales activities and the materials with the individual client. In the same way, correlation with sales results can be drawn.
Why incorporating downstream data is important?
A CRM can be enhanced with data analytics with the incorporation of the downstream data back into the application itself. It can take various forms. In the insurance industry, the claims detail can be placed into the client profile for risk assessment. Or an external data can be integrated into a client profile, which offers indicators that the client has seen some major event and may benefit as well in the future.
For example, a service vendor is expected to develop alerts for a specified representative to opt for follow up if it is found that a client will be opting for a merger, acquisition or even moving into a new market. The service or software domains can keep track of the usage rates or even support requests and also making these metrics available within the CRM tool. When few financial KPIs can be derived from the CRM tool, then such a provision should be available for entering the same data into the tool so that the sales manager are able to better manage their business. This helps in weaving back a company’s data into the valuable enterprise application.
Looking at the future
There are quite a few interesting possibilities for the future of CRM analytics. Offering coaching to the sales team could help in introducing new perspective if the sales presentations have been recorded. It also becomes possible to analyze the ‘word clouds’ for differentiating few message patterns such as successful one and also unsuccessful one.
For example, if a retail shopping tour is driven by the use of a tablet or a smartphone. An assistant will always be available for answering to questions and also understanding the buying needs. When a CRM adopts more individualized experience, it helps in identifying the client patterns.
There are numerous ways of making the sales process smarter via the intelligent usage of the data analytics. Although, selling is considered as part of soft skills, but the post digital age has offered no shortage of different ways sales can be reviewed. But customer centric and successful firm will ask important questions such as do clients from different region display different buying pattern in regard to the sales interaction? How a client base should be segmented for optimizing return? Is it possible to lower the sales cost without affecting the financial returns? The answer to all these questions is considered as a crucial part of CRM analytics apart from successfully positioning it as a valuable commodity.
Since companies invest a major portion of resources in CRM, it is essential that companies carry out a proper check on the software/tool for bringing out the best. There are numerous ways available for optimizing the CRM implementation, but it has been found that data analytics mainly provides exciting opportunities for introducing innovation in the sales process.
CRM data analytics can also help a business to push for a stronger sales process along with empowering the field personnel with smarter tools. It can be successfully carried out not by simply studying the available CRM data but by strengthening the data with extra details.
Initiate account planning
The basic premises for selling goods and services have been consistent, which means converting the opportunities into closed deals. But as the salesforce evolved and the potential for a national clientele, the sales process’ complexity exploded. Important sales activities now comprise of territory alignment, client segmentation and also account management at multi stages. It has been found that account planning gives the resources of the sales team to the clients and also the potential clients in an effective manner. It has been found that CRM analytics can prove helpful for the process by combining the previous sales activity data with the historical sales results and also other data influencers. When a sales team is asked to name the top 10 clients, the response should come quickly. But are they in a position to tell you about who the top 10 clients will be in the next quarter? But with the right sort of business intelligence, it becomes possible to answer questions easily. This way of information collection is an efficient way for companies to opt for segmentation of clients into prioritized groups.
Developing an improved sales call
CRM analytics has been useful for ensuring that a sales interaction is good. Creating an improved sales call is dependent on the right CRM details architecture. A CRM tool should not be able to keep track of the accounts and contacts but also the actual sales materials offered to those clients. There are numerous advantages of this setup. For example, the sales and marketing materials can be easily stored in the central location also consumed by the filed agents as and when required. Cloud based CRM tools make search of the email folders for the recent version of a PPT easy and quick. In this model, the usage and also the adoption rates of such materials can be easily kept track of. Few regulated industries can also automate the compliance procedures through the digital consent pacts when a client checks out certain content.
In regard to the consistent improvement, the feedback for the sales presentation materials can be collected from the client as part of the sales call. This feedback can be found in the CRM repository to bring improvement in the future. It has been found that the smarter calls have been developed by offering the client with the appropriate cross selling opportunities. It has been found that data analytics play an important role in deciding the cross sell chances. A company with enough order history and also client dimension data, models can be developed that will offer a suggestion list of extra products bought by the similar clients. But one of the most essential factors from the analytics side is for associating both the sales activities and the materials with the individual client. In the same way, correlation with sales results can be drawn.
Why incorporating downstream data is important?
A CRM can be enhanced with data analytics with the incorporation of the downstream data back into the application itself. It can take various forms. In the insurance industry, the claims detail can be placed into the client profile for risk assessment. Or an external data can be integrated into a client profile, which offers indicators that the client has seen some major event and may benefit as well in the future.
For example, a service vendor is expected to develop alerts for a specified representative to opt for follow up if it is found that a client will be opting for a merger, acquisition or even moving into a new market. The service or software domains can keep track of the usage rates or even support requests and also making these metrics available within the CRM tool. When few financial KPIs can be derived from the CRM tool, then such a provision should be available for entering the same data into the tool so that the sales manager are able to better manage their business. This helps in weaving back a company’s data into the valuable enterprise application.
Looking at the future
There are quite a few interesting possibilities for the future of CRM analytics. Offering coaching to the sales team could help in introducing new perspective if the sales presentations have been recorded. It also becomes possible to analyze the ‘word clouds’ for differentiating few message patterns such as successful one and also unsuccessful one.
For example, if a retail shopping tour is driven by the use of a tablet or a smartphone. An assistant will always be available for answering to questions and also understanding the buying needs. When a CRM adopts more individualized experience, it helps in identifying the client patterns.
There are numerous ways of making the sales process smarter via the intelligent usage of the data analytics. Although, selling is considered as part of soft skills, but the post digital age has offered no shortage of different ways sales can be reviewed. But customer centric and successful firm will ask important questions such as do clients from different region display different buying pattern in regard to the sales interaction? How a client base should be segmented for optimizing return? Is it possible to lower the sales cost without affecting the financial returns? The answer to all these questions is considered as a crucial part of CRM analytics apart from successfully positioning it as a valuable commodity.