The traditional image of a successful salesperson is someone who sets off (probably with a fedora and briefcase), armed with charisma, persuasiveness, and a belief in what they are selling. While amiability and charm certainly play a role in sales today, analytics has emerged as the most important tool in any sales team’s box.
Data is at the core of the modern sales process. Making the most out of data means extracting the right insights to figure out what is working and what is not. Without analytics in place to do this, sales and marketers essentially operate in the dark, guided by intuition. As adoption of analytics continues to grow, and as the tools become more sophisticated, charisma isn’t enough; failing to integrate analytics throughout the sales cycle represents a crippling competitive disadvantage.
Research from McKinsey, published in an eBook titled Big Data, Analytics, and the Future of Marketing & Sales, found that companies that effectively use Big Data and analytics display productivity rates and profitability that are 5 – 6 percent higher than their peers. Moreover, companies that put data at the center of the marketing and sales decisions improve their marketing return on investment (MROI) by 15 – 20 percent, which adds up to $150 – $200 billion of additional value.
Let’s explore the three main reasons why sales teams fail without analytics.
1. A scavenger hunt in the dark
Without analytics, figuring out how to convert leads into customers is largely rooted in guesswork and/or word-of-mouth. Relying on your gut, rather than data, means wasting a significant amount of time and energy on the wrong people, topics, presentation formats — or all of the above. Moreover, sales reps are not only striving to convert leads, but to convert them into long-term, valuable customers.
This is not something that can be done manually because there are too many variables and subtle correlations. No two leads are alike, and their interest may fluctuate and evolve from day-to-day. Sales reps, try as they might, are not mind readers. Fortunately, analytics can shed some light.
Analytics can yield engagement data, revealing what works and what doesn’t, so sales people enter every meeting prepared. Learning from the most valuable sales conversations enables reps to constantly improve. For example, analytics can determine if certain presentation slides garner a stronger response than others, of if interest drops off after a certain amount of time has gone by. This visibility enables reps to boost their close rates and shorten sales cycles. Analytics can also uncover trends and increase pipeline accuracy, by using data to understand which deals are actually likely to close.
2. Stuck in the mud
Marketers often get stuck in constant production mode. They try to generate as many leads as possible, send them onto sales to pursue, and then focus on anecdotal feedback about what is supposedly working. However as mentioned above, a significant majority of these leads never convert. Without analytics, the “why” remains a mystery, and marketers do not learn from their mistakes.
Engagement analytics provide sales and marketers alike with quantitative feedback, so they can zero in on what’s really going to matter. They offer unprecedented visibility into customer preferences and this allows teams to get smarter and more effective over time. What a sales team thinks is the strongest selling point may not actually be the strongest selling point, and their efforts could be stalling as a result. Engagement analytics are a powerful tool to unstick them by changing their POV, and providing hard data about what content and strategies have the greatest impact. Once they understand the customer journey, they can optimize their process accordingly.
3. Mass marketing
Whether you are selling tee-shirts or enterprise accounting software, personalization strengthens your sales pitch. Buyers today are so inundated with pitches that they have neither time nor interest in products that are not directly relevant and suited to their unique needs. However, every company, and even every buyer, is different, which makes understanding their needs and personalizing pitches accordingly a nearly impossible feat at scale, at least without analytics to help.
Sales and marketers have a wealth of data at their fingertips from both internal and external sources that can help uncover what prospects want and need to hear. Using Big Data, analytics, and machine learning, companies can tailor their message to each potential customer. In this way, analytics distinguishes your pitch from the crowd and increases the chances that a deal will close.
Throughout the sales process, analytics makes sales and marketing teams smarter, more efficient and more effective, not to mention more aligned, which is linked to sales productivity. It is a necessity in today’s competitive landscape, and as predictive analytics takes off, will only become more essential.
Businesses are increasingly relying on predictive analytics to synthesize data, optimize their operations, and improve decision-making. Gartner’s Hype Cycle for CRM Sales (2015) pegs Sales Predictive Analytics as a high-value technology over the next two to five years, and Forrester Research found that nearly two-thirds of marketers are implementing or upgrading predictive analytics solutions today or plan to do so in the next 12 months. Predictive analytics takes sales teams from reactive to proactive. Without availing themselves of these tools, companies will find themselves left in the dust.