Integrating CRM Data into the Enterprise
Thinking back to the early days of CRM and looking at the recent announcements by the major players, it is amazing to see the progress we have made when it comes to integration, platform extensibilities, and embracing CRM as mission-critical to the success of your organization. These enhancements, innovations, and outlooks are a welcome sight to those of us who advise businesses on the value of data and how and where to leverage it for competitive advantage.
So how, specifically, should businesses be leveraging their CRM data? Which parts of the organization can be empowered by it, and which methods should be applied to take advantage of evolving technologies like artificial intelligence, analytics, and collaborative capabilities?
Here we’ll run through some use cases, but before we do, let’s cover some of the assumptions and cautionary tales that others have experienced when proceeding down this path. The first thing to consider is the quality of your CRM data. Data stagnancy, data accuracy, and white space within your data are all important factors; most firms will find that they will struggle in each of these areas. And when presenting data through different lenses to different constituencies, the impact can be adverse if the data is telling the wrong story.
Unfortunately, in some of these areas, there is no easy fix. The same people responsible for entering or validating data can have competing priorities, like helping customers with service issues versus bringing in new business. And in the current climate, many firms are short-staffed and facing fierce competition. So how could you address this situation? One way is to leverage AI. While AI is commonly used to predict next best actions or make suggestions regarding external situations, there is no reason not to leverage these capabilities to help manage your CRM data.
Let’s take a common scenario. Your firm wins a significant opportunity, and the team selling is using CRM effectively, putting in activities, logged against the people they interact with through the process, and successfully mapping out their engagement with the right decision makers to reach a successful conclusion. The deal is within an ideal target industry and there are no identifiable extenuating circumstances around this win. Using AI enables you to then work backward and look at other similar deals in order to create a data profile that can be used to train and make recommendations across other accounts. This way you can identify where there are data inaccuracies, white spaces, or failures to target the right contacts.
Using AI as a tool to help your teams pursue the results they want, based on success specific to your business environment, is leveraging CRM data in a way that makes you better without necessarily having to address all of the data challenges you might have. These scenarios can be replicated across service and marketing as well. The beauty of having analytics and collaboration capabilities within your platform is that AI can work behind the scenes and visualization and communication can happen concurrently to bring these insights to life.
Pairing AI-powered tools with CRM data can be likened to “just-in-time information.” As in the days when just-in-time manufacturing was all about having the right resources in the right places at the right times to maximize throughput, using information in the right time and the right place to direct our efforts or make business decisions is a very powerful asset.
Now let’s take a look at how CRM data can be leveraged elsewhere in the enterprise. One interesting scenario is with human resources. Many insights can be drawn from CRM data for both sales and service environments, particularly the level of effort needed to produce results. HR teams are constantly juggling how many people to hire for different teams and often rely on traditional assessments by people. But data will always tell its own story, one that can be evaluated by AI, which can then make recommendations based on current circumstances. Imagine having your HR teams and managers notified to changing business conditions and thus equipped to proactively staff accordingly.
Demand forecasting is another area where CRM data can have significant value, in both product- and service-centric environments. As illustrated by recent challenges in supply chains for manufacturers or the competition in hiring for services, production and capacity is very elastic and constantly changing. The same is true for the level of effort it takes to sell and service our customers. Having analytics and AI capabilities monitoring and visualizing these changes can be instrumental in making both manufacturers and service organizations more efficient and profitable.
Yet another area is talent development. Once again CRM data can show you many interesting aspects of what individual team members are doing and where they can use support and guidance. Regardless of our aspirations, not at all team members get the same level of support, and the data, with the help of analytics, will bring that to the surface. CRM data can thus uncover opportunities to better manage your personnel.
Hopefully these different scenarios provide some insight into what is possible with CRM data in a number of circumstances. Data is the foundation, and if it is good and managed effectively, it can become a competitive weapon in an increasingly competitive world.
Danny Estrada is the vice president of consulting at Rare Karma. Throughout his career Danny has been a CRM evangelist and expert at leveraging technology platforms to create business value. He has been a senior director at KPMG and a thought leader for Salesforce and Microsoft, and he was published in an industry white paper by the Harvard Business Review. He also holds an Executive MBA from the W.P. Carey School of Business at Arizona State University.
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