In last week’s post, we discussed the importance of leveraging business intelligence/analytics (BI/BA) tools to extract quality client data that can be used to drive stronger customer engagement and boost brand loyalty and identity. As organizations seek to increase their analytical investments in the upcoming year, many may be wondering how to integrate such processes into their existing CRM systems. The good news is the tools you already have in place to store and manage customer data can easily be customized to align with BI/BA insights. To maximize your investments in both CRM and BI/BA resources, the key is to maintain a centralized, focused data strategy centered on clean, actionable data—information that can be directly applied to your business goals and is free of conflicting, misinterpreted or unusable statistics.
Sorting through the immense amount of feedback provided by BI/BA tools can be overwhelming—imagine tracking the online activities and preferences of just one of your clients, then multiply that by your entire audience base. Data “cleansing” tools are designed to simplify the process—sorting through virtual piles of information to clean, enhance and back up the data deemed as critical into your CRM system. A major part of an effective data strategy, these tools are invaluable in their ability to simplify and streamline client information, facilitating CRM efforts and ensuring more direct, relevant analyses. Rising in popularity and use, such resources are quickly becoming a necessity. According to a recent industry leading survey, 71 percent of companies plan to increase their investment in analytics in 2015 (with 20 percent planning a substantial increase). Additionally, 51 percent of respondents are currently invested in data cleansing tools, and 26 percent plan to invest next year. This consideration comes at a critical time, as 38 percent of respondents were not confident in their current data instances.
Obtaining clean and actionable data not only makes current customer engagements easier and more direct—rich, informative client information is key to the success of ongoing and future campaigns as well. Whereas traditional customer engagement methods focused on reactive responses—such as a customer service inquiry pinging support personnel to action—new systems focus on predictive analysis, examining existing customer preferences to predict how a first-time buyer may act, and using this knowledge to drive stronger engagement efforts. The concept is relatively fresh, and companies are still learning how to integrate such activities into their current campaigns. In fact, only 19 percent of survey respondents rated their use of predictive analytic as mature. Similarly, in a recent Aberdeen Group report tracking the use of mobile analytics, while 80 percent of companies cited use of web analytics, only 31 percent were currently deploying predictive analysis techniques within their organizations.
This is where robust CRM integration is key—leveraging existing information on your contacts and their history with your organization provides an excellent background for predictive analytics, but only if the data stored is useful, relevant and informative, another reason data cleansing and sorting is crucial to an effective data strategy.
Your clients are talking to you—make sure you’re capturing what they’re saying in the purest, most informative way possible. Only then can you review and analyze it to make strategic company decisions and ensure your goals are aligned with theirs.
If you’d like greater detail on the performance benefits users are seeing from data strategies, we’d love to speak to you. In the meantime, to learn more about how our seasoned CRM consultants can deliver this functionality to your business, please contact any member of our consulting team at email@example.com. We also encourage you to contact Tokara’s VP of Business Development, Mark Fillingim, directly at +1 972-719-0213.
Bluewolf, “State of Salesforce 2015 Report,” http://www.bluewolf.com/landingpage/sosf_report/
Aberdeen Group, “Mobile Analytics: Precision Marketing Across Mobile Touch Points,” August 4, 2014, http://www.aberdeen.com/research/9364/RR-mobile-analytics.aspx/content.aspx