How To Leverage Predictive Marketing Analytics To Increase Sales
Once a niche capability afforded only by big ticket players like IBM, SAP, Target and Amazon who had the reserves to pump into expensive data crunching technologies and analytics experts, predictive analytics is now being democratized. SaaS services have made it easier for smaller organizations to leverage predictive analytics to better prioritize sales leads, identify which products a prospect would be most likely to buy, nurture contacts who are most likely to buy and develop more reliable sales forecasting.
Companies that use predictive analytics have historically outperformed those that don’t in two important marketing metrics: incremental sales lift and average clickthrough rate. Predictive analytics users can generate two times the incremental sales lift from a campaign compared to competitors that don’t leverage predictive analytics. Marketers using predictive analytics also record much higher average clickthrough rate from their marketing campaigns, producing better results via more accurate segmentation of the target market and the ensuing targeting of marketing offers.
However, the proliferation in the number of market drivers is putting pressure on marketers to evolve their digital marketing practices. The explosion of customer data captured by enterprises and the increase in the number of digital communication and social channels makes it pertinent for marketers to adopt new data strategies to make more accurate decisions and react to market dynamics quicker than the competition. Now each customer’s path to purchase has more touch points, enabling a rich data storehouse and key insights into customer behavior. Yet even with all the data available few companies can extract maximum value from their customer interactions. To leverage the highest quantifiable value from these touch points, organizations must learn how to integrate all these touch points and harness data big and small so businesses can use data to look forward, rather than just at past performance.
Through innovations in modeling automation and data visualization, advanced predictive marketing analytics tools empower digital marketers and analysts to track statistically important variations (dips or spikes) across any metric, so they always know which metrics and data are the most important and which levers will drive positive outcomes. Predictive analytics allow micro-segmentation of the target market into actionable buyer personas based on geographic, psychographic and demographic profiles, so that marketing campaigns never miss high-value visitor segments. Accurate lead scoring helps predict and target those customers that are most likely to perform an action, such as convert, churn or respond. Predictive analytics also enable greater relevance & personalization by optimizing engagement across customer execution points, from search to social.
Predictive marketing analytics can be equally useful in growing existing accounts and closing new ones. From first touch to conversion, predictive marketing analytics give full visibility into lead progression along the purchase path, so that marketers can develop data-backed SLAs to keep everyone in on their toes. With the ability to see which marketing activities contribute to revenue, marketers can optimize campaigns and more accurately forecast how, which and when leads will translate into revenue and sales. This information enables marketers to determine revenue levers, and adapt campaigns quickly to ensure that sales get the promised volume of high quality leads.
In the End
Marketing automation and predictive marketing analytics offer a huge advantage to organizations that get it right and with the right tools and the right team at the helm, there is a fair chance for organizations to achieve it. And those who can even record high double digit increases in leads, opportunities and sales. But you need to get cracking immediately. It’s a data driven world, and how you fare in it will depend on how well you can manage and leverage maximum value out of your data. And to achieve that you must drive the integration of analytics into every function of your organization.