How to Drive Sales Without (or With Fewer) Salespeople
No business can survive without sales, let alone thrive. But as it turns out, sales remains a major weak point for most modern organizations.
According to the most recent Talent Shortage Survey by ManpowerGroup, sales representatives are one of the top three most difficult jobs to fill. But when companies do manage to fill the position, many of them simply can’t get the job done. A recent study by The Miller Heiman Group and CSO Insights revealed that only 53 percent of salespeople met their quotas in 2017.
Fortunately, by putting in some extra legwork and leveraging the technologies at their disposal, companies can actually drive sales without (or with fewer) salespeople.
Here’s how…
Prioritize Data Collection and Analysis
In today’s digital world, there is more opportunity than ever for businesses to sell their products using data-based insights to better target customers, improve their products and build brand loyalty. Among the many types of data that businesses should collect, these are the four most relevant to help drive, or ease, the sales process with fewer salespeople–
Customer Behavior Data
How many times has a customer visited the company website? Have they downloaded content? Signed up for a trial? Companies can use this type of data to decide which leads have the highest probability of conversion, and focus their efforts on those customers.
Product Usage Data
- How often do customers log in?
- How exactly are they using a product?
- Do they stop using the product at a certain point?
This data provides invaluable feedback as to how companies can improve their products to make them more attractive for both existing and potential customers.
Customer Support Data
How frequently are customers interacting with your sales and support teams? What are their most common complaints? Suggestions? Customer support data can highlight certain pain points along the customer journey that are impeding the sales conversions or upsell opportunities.
Purchase Data
What is the average basket size of customers’ purchases? What products or services are the most popular?
Many people forget about this type of data, but it is ultimately what determines buying preferences – and a customer’s lifetime value. The most valuable data falls in the extremes: those who spent 10x more or less than the average.
Read More: Interview with Sandie Overtveld, Vice President Sales, APAC at Zendesk
The more businesses understand this data, the more they can understand exactly what a good customer is, how they behave, and what separates them from a bad customer.
Customers that have a large number of support tickets, for example, are often the ones with the lowest dollars of revenue earned. With insights such as this, businesses can focus more on closing strong leads and increasing the lifetime value of good customers, and waste less time on weaker opportunities.
Doing this, however, requires companies to go beyond lead scoring, and instead take a full lifecycle view. Marketers and support teams should keep a close eye on customers who have paid a lot of money, as well as those who are about to stop paying a lot of money. This allows them to improve the lifetime value of customers with the most earning potential, and thus sell with fewer salespeople.
Ultimately, data can provide marketers and salespeople with a new, granular level of insight – highlighting opportunities they may not have seen otherwise. In doing so, they can learn what type of customer responds to what type of sales tactic, and reduce the number of salespeople needed by making each campaign more effective.
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Sell from Inside Your Product
In addition to better targeting the highest value customers using insights from data, companies can reduce the number of salespeople they need by taking an omni-channel approach to the sales process, aided by that very same data. More specifically, they can implement new strategies to create selling opportunities from inside their products, and increase the revenue they generate from existing customers by communicating with them at key moments in the customer journey.
For example, think of Amazon’s “frequently bought together” suggestions, which present users with a list of items that go along with the purchases they are about to make. Expedia is another example, sharing with users how many others have looked at the same listing in the past 24 hours. For customers, this adds a sense of urgency that incentivizes them to purchase then and there, at a moment when they might have otherwise abandoned the purchase.
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As these examples illustrate, the ability to sell from inside a product also depends heavily on data. However, in order to leverage the data effectively, companies need to have it aggregated in one place, giving them the ability to both simplify and observe the end-to-end customer experience. This means that wherever a customer is interacting with a product – be it on mobile, web, TV or anywhere else – there is a consistent experience that makes it not just more enjoyable for them, but also easier to create sales opportunities at the perfect moment.
Read More: Interview with Sandie Overtveld, Vice President Sales, APAC at Zendesk
Netflix best embodies this idea, allowing users to pick up their shows right where they left off, regardless of the device they are using. From there, they are able to make accurate recommendations on what other content users might be interested in watching.
To similarly begin selling from inside their products, companies can implement chat systems that allow them to step in and interact with customers at certain points along their journey when they see an opportunity to make a sale. On the other hand, automated in-app selling tools have also emerged as a newer technology that allows companies to do this without involving any humans in the process.
Use Automated Referral Programs
A final strategy for companies to reduce the number of salespeople is to leverage referral programs. Referrals are one of the least expensive – not to mention easiest – ways of acquiring customers, given that a company’s existing customers are the ones actually doing the sales work.
This strategy works particularly well for businesses with organically growing audiences – that is, for businesses whose products are being promoted on social media without any incentive or motivation. It also works for businesses with low-friction products that people can buy very quickly without needing to involve a salesperson.
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For these types of businesses, referral programs significantly reduce the amount of resources companies need to invest in sales. Moreover, automated referral programs including our own and many others can further reduce the need to involve humans in the process. These work particularly well for high-volume B2C products, as most B2B companies generally have lower sales volumes that can be managed easily with a manual process.
But for any effective referral program, an important component is to make sure the reward is worth it, relative to the price of the purchase. As such, companies should start with bigger rewards and then slowly test reducing them over time to make sure they gain initial traction and don’t suffocate a referral program by being too financially conservative.
Additionally, it’s important to note that the type of reward should vary depending on the product. For products that have multiple users but only one buyer, like family subscriptions, for example, gift cards are more effective as the person being rewarded may not be the person paying the bill. And for consumer-to-consumer referrals,non-cash incentives are 24 percent more effective. Cash, on the other hand, is typically better for influencers, partners and affiliates.
Using these strategies, companies whose sales teams are struggling to meet their quotas – or companies who don’t have the budget for large sales teams to begin with – can effectively drive sales for their organizations. At the end of the day, it comes down to the fact that it’s not always about acquiring new customers, but identifying the best ones and making them even better.
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