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Figuring out the perfect moment to reach customers has always been the main challenge in sales. Thanks to new technologies and platforms, the buying journey has become more complex. Every day, sales teams across the world try to answer these questions:

  • Which is the best day to ring a customer or lead?
  • When is the optimal time to call?
  • Which days and times should be avoided?
  • How to make the most out of the conversation once the lead answers?

What the sales industry and researches say

There is no shortage of industry and company reports attempting to provide answers. Here are some findings from three of the researches we encountered:

  1. CallHippo analyzed the data of their 1,000+ clients containing 13,750 call attempts and 1,350 successful conversations. They found that Wednesday is the best day to call, while Friday is the worst. The best time to call is between 4 to 5 pm, while between 1 to 3 pm is the worst.
  2. Dr. James Oldroyd, a Professor at Sung Kyun Kwan Graduate School of Business, with the Kellogg School of Management conducted a similar study in 2007. It was participated by companies from 40+ industries. The study revealed almost the same results. Friday is the worst day to make calls, while Thursday is the best. The worst time is between 1 and 2 pm, while the best is between 8 to 9 am and 4 to 5 pm.
  3. Steve Richard on Harvard Business Review shared a tip of separating sales calls into two activities. First, is to prospect from 10 am to 5 pm. Second, is to call blitz before 8:30 am and after 5:30 pm. Other great times to call are “five minutes before the top of the hour, catching the executives before their next conference call meetings, and holidays like President’s Day, when executives are likely to be in the office and other business may be slow.”

What we say—the optimal moment varies and data matters

Different researches reveal similar but different things. It’s because successful sales calls do not only rely on any particular day and time, but also on what sales know about the customers. And that includes being aware of their availability and business needs.

A Telfer School of Management Sales Engagement Study found that, contrary to popular industry findings, all business days and times have similar response ratio from leads. It analyzed 130,000,000 interactions with 45,000,000 distinct contacts including 4,000,000 web leads from 2005 through 2017.

The study also revealed that the most significant factors of success are follow-up calls and call duration. “For every increase in minute in call duration, there is 6 times better odds of success with the lead.”

How can sales make relevant follow-ups and lengthen call duration? It’s using data to know the customer on a deeper level. This makes sense. In fact, a Dun & Bradstreet publication revealed that the sales calls that buyers do pick up “do little to spark their interest.” Buyers (29%) feel sales fail to do basic company research and contact them at the wrong time.

To prevent that from happening, sales need to leverage customer insights to determine who to call, at what time, on which channel, and what to talk about. This is what we do at OptimalQ. The more sales understand the customers, the better they can engage them and make the call more relevant and meaningful.

While the quantity of sales calls matters, the gamechanger today is quality. Customers today expect more from sales. Beyond being sellers, sales are transforming to become trusted and knowledgeable advisors. It’s high time to better connect with leads and customers, and data is the answer.

Increasing the likelihood of success, real-time customer and availability insights help sales perfect the timing and channel for engagement. In the end, the optimal moment to call customers is when sales, armed with powerful data, add value and establish connections that speak to their needs.

At OptimalQ, we enable companies to engage with leads and customers when they are both physically and mentally available. Using AI and machine learning algorithms, OptimalQ identifies and analyzes user behavior, and translates it into availability insights that can predict the most effective times to engage with leads and customers.