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StrategicRoadmap ForSales AnalyticsGartner for Sales Sales analytics functions often struggle to deliverdesired commercial impact due to perennial challengeswith low data quality and poor stakeholder engagement.To achieve their full potential, sales operations leadersmust prioritize data governance, data literacy andadvanced analytics technology. Overview Key Findings •The need for collaboration among commercial functions is growing asbuyer preferences evolve. From an analytics perspective, seller-providedCRM data may no longer provide sufficient intelligence on buyer behaviorand intent. Sales analytics functions that don’t fully understand theinformation needs of the larger organization are missing the opportunityto share insights among commercial functions to drive more cohesivedecision making. 53%of surveyed organizationsattribute poor sales dataquality to inaccurate andincomplete data •Fifty-three percent of surveyed organizations attribute poor sales dataquality to inaccurate and incomplete data. Unfortunately, just 51% haveestablished a formalized data governance body. A lack of data governancemakes it difficult for sales operations to improve data quality and buildtrust in their analytical insights. 51%have establisheda formalized datagovernance body •The technology delivering sales analytics most commonly consists ofreports and dashboards residing in native sales systems. Expectationsfor unlocking analytical insights through more advanced technology,particularly by improving data integration and deploying artificialintelligence (AI), are on the rise. Sales operations leaders are challengedto identify the technologies most appropriate for their organizations. Analysis Recommendations Sales operations leaders responsible for improving sales analytics must: Sales operations leaders responsible for sales analytics are faced witha widening gap between their stakeholders’ need for data-based insightand today’s status quo of data and analytics. •Ensure executive support for transforming the sales analytics functionby designing a clear and compelling vision for sales analytics that reflectsthe needs of all commercial functions.•Establish a formal data governance program to monitor and promotedata quality, oversee analytics projects and enable high-qualitycollaboration among all sales analytics stakeholders.•Initiate a cross-functional data literacy program to ensure that consumersof sales analytics derive meaningful value and consistent interpretation.•Develop a multiyear roadmap for sales analytics technology by identifyingand prioritizing specific use cases where advanced technologies offer thehighest potential commercial impact. A number of factors are contributing to this growing challenge: •Suppliers are facing unprecedented disruption and are looking to analyticsto help them make sense of changing buyer behavior.•Buyers are increasingly opting to interact with suppliers through digitalchannels, making it harder for sales analytics functions that rely onseller-provided pipeline data to glean insights.•Sales operations leaders cite the complexity of business and its underlyingdata as a top obstacle for sales analytics, which will be exacerbated asnew systems and data sources are added to the technology stack.•Suppliers intend to invest in AI to take advantage of more predictive andprescriptive analytics, but are unsure where (i.e., with which use cases)to begin that journey. Strategic Roadmap for Sales Analytics Sales operations leaders can use our roadmap to set their vision for bridging the gaps between their current and future states. Current state Future state •Augmented analytics and the declineof the dashboard•A host of new data inputs unlockedby X analytics (technology that candetect, evaluate, extract and organizedata from written text, spoken wordsand video recordings)•A seamless buying experienceenabled by continuous intelligence•Democratization of data scienceand AI•Personalization displacingone-size-fits-all analytics •Sales analytics primarily targetedto the sales function•A common challenge posed by datagovernance•Prevalence of native sales systemreporting•Data literacy lowest at the seller level Gap •Limited participation in analytics selection and design•Analytics adoption inhibited by low data quality and trust•Incomplete integration of channel interaction data•Gaps in data literacy limit ROI on sales analytics Migration plan •Align stakeholders on a vision and prioritization of use cases.•Establish data governance to enable collaboration.•Elevate levels of data literacy throughout the organization.•Prioritize technologies for specific sales use casesbased on potential business impact. Current State of Sales Analytics Sales analytics primarilytargeted to the sales function. Data literacy lowest at theseller level. Native sales system reportingprevails. Data governance poses acommon challenge. Today’s sales analytics functionsare primarily focused ondeliver