“The adoption of a data-driven approach can also lead to increased profits - up to 6% more profit than your competitors."
The sales team is an indispensable part of any business. They are the first point of contact that connects the prospects and potentially turns them into customers.
Every move made by the sales team impacts the business revenue and plays a significant role in maintaining clients’ relationships.
Traditionally, clients would walk away with the sales associate whenever they switched jobs. A salesman played a much more important role than a brand name.
However, now things are different!
Neither the client nor the salesperson is blindly dependent on each other. Let’s understand this development in detail.
How have sales progressed with sales analytics?
Both seller and buyer have access to more information than ever. Hence, both find lucrative opportunities without depending on one another.
As far as sales function is concerned, it evolved from intuition and relationship-driven to a strategic and informed process. Salespeople no longer rely on customer sentiments but trust methods that continuously hint at new selling opportunities from the same client.
The above transition resulted from the data-driven approach that made sales a proactive function rather than reactive. Data turned around sales teams and their goals, facilitating more sales opportunities that were earlier farsighted.
Marrying customer data with sales analytics is another turning point in the sales fraternity. It automatically creates a new outlook for sales approach and drastically improves customer experience.
And there are plenty of examples to back the contribution of analytics in improving growth, productivity, and efficiency.
One such case was with a large telecom company in the UK. They observed that only 60% of their sales folks were hitting their sales targets. The company was seeking a way to improve sales conversions along with better quality of sales conversation. After the company adopted and started tracking an Associate Performance Index, they noticed a staggering 32% increase in sales target by 92% of the sales associates and an overall increase of 15% in sales
Evidently, data-driven sales and analytics can alter the story of your organization. Also, you don’t want your sales guys jumping ships with unfair and unstructured KPIs because data can keep your sales associates motivated and well-incentivized.
Now, let’s closely look at a few reasons why companies invest in sales analytics.
Why invest in sales analytics?
To unlock valuable and relevant insights that enable better selling, you need to invest in sales analytics.
A study conducted by McKinsey on fast-growing companies leveraging digital analytics to empower salespeople reports that 53% of these companies rated themselves “effective” while making decisions based on data analytics.
With such transformational outcomes, sales analytics becomes a pivotal element in sales. Let’s see a few reasons why investing in analytics is your best bet:
1. Improve prospecting and lead generation
You’ll be surprised to learn, at least 50% of your prospects are a terrible fit for your product!
But you wouldn’t want to face that, isn’t it?
That’s where sales analytics comes into the picture. It helps in identifying the ideal customer profile for your salespeople. The data-qualified vetting process qualifies prospects suitable for the product and, similarly, locates target industries that host buyers that’ll most likely convert. Using the information, sales reps can focus their marketing efforts on prospects that fit ideal customer profiles.
Quality data sets and analytics metrics improve the accuracy of lead generation and aids in the identification of the right customer at the right time. Off late, some brands are pushing this further by employing lead-scoring methods based on historical and external data sets on prospects and their industry.
2. Forecasting and predictive insights
Sales analytics has introduced forecasting and predictability in sales.
Sales revenue forecasting is utilized in developing budgets for capacity plans and hiring. Forecasting significantly contributes to sales performance management- territory reassignment, pipeline management, quota planning, incentive programs, and channel strategies.
By applying sales analytics, leads that are likely to convert are more predictable, locating suitable sales channels is more accessible, and identifying the most prospect-friendly engagement time is possible.
3. Coach sales resources
Complete access and visibility into sales conversations; allows managers to identify gaps that usually slip away because the analytical data is the missing piece to the coaching hustle. With conversation data, managers can bridge the gap in sales performance and keep a tab on emerging tabs and opportunities.
With analytics-driven sales coaching, reps:
- Learn about selling strategies in-depth
- Improve objection handling and negotiation skills
- Win deals by applying the right selling tactics based on historical interaction.
- Determine if the prospect needs nurturing or if they are ready for sales
- Improve discovery calls and extract better information to deliver a personalized experience
- Reduce prospect-to-customer conversion time
- Discover unique up-selling and cross-selling opportunities while interacting with existing customers.
Additionally, the sales manager can assist in sales presentations, demos, and product pitches. In parallel, amend the content for sales based on feedback received from sales conversations.
The final result is even sweeter; sales managers create a robust information repository that lists accurate information.
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4. Recognize upselling and cross-selling opportunities
New reps often fail to smell additional opportunities on sales calls. However, AI-based sales analytics can analyze a substantial amount of data to provide actionable insights.
With a sales analytics strategy in place, you can determine how to keep your relationship with customers, even after the business has sold. As a result, your sales team can upsell and make existing customers repeat customers, helping them maintain relationships.
5. Decrease in non-selling and support activities
In 2018, Linkedin researched 721 reps, which determined that 65% of their time was spent on non-selling activities. Sales reps spend more time on non-sales activities such as sales forecasting, prioritizing leads, managing pipelines, etc.
On implementing the sales analytics, the sales team can automatically make room for more strategic activities- pipeline analysis, networking, deal closing planning, nurturing existing relationships, create compelling proposals, and make time for learning & development.
6. Identify risks and threats early
Another ignored advantage of sales analytics is showing risk alerts on time. Analytics can help in experiencing a single, uncensored view of all your deals, making it faster to quickly identify and act upon the deal risks such as no communication with the buyer for 2-weeks straight.
7. Move to a proactive sales approach
Sales analytics changes the way sales teams approach deals. By implementing analytics, you choose to shift from reactive selling to proactive selling.
Sales leaders can stress forecasting and predictive selling and allow analytics to hold a central role in all sales decisions. Tools such as conversation intelligence software and deal intelligence make more impact when the mindset shifts from reactive to proactive. This means, time spent on guesswork and biased decision-making can also be reduced.
Proactivity not only addresses risks on time but successfully holds on to customer opportunities within the organization.
Sales Analytics for better conversations
42% of sales reps believe they lack deal information before making a call.
One area sales analytics has shown remarkable success is conversation intelligence. It’s taken sales conversations to a new frontier, making sales calls much more helpful for reps.
You should keep a close eye on these features of your sales analytics tool:
- Access Call Moments- Create a personalized experience by accessing key topics and portions of the call.
- AI-driven- The AI-based conversation intelligence refines call analytics and makes recommendations easy to implement. It is possible to analyze 100% of phone calls automatically and generate AI scores for each.
- Performance Statistics- Sale conversation statistics such as the talk ratio, longest rep monologue, longest customer monologue, patience, interactivity, question rate, and more are accessible after each sales call.
- Access to Deal Intelligence- Sales conversations can be more strategic and manipulated by adding a deal intelligence dashboard to conversation intelligence recording software. Getting deal highlights and red signals will be a breeze.
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