A Quick Guide to Forecasting Sales Using Artificial Intelligence in eCommerce

Posted by Monis Khan on Nov 14, 2019 3:14:03 PM

AI can scan large volumes of real-time and historical data, to identify the most lucrative sales leads. Learn how artificial intelligence is shaping sales in eCommerce.

Sales forecasting is a critical building block of a successful eCommerce business. Managing the cash flow and human workforce, enabling a smooth supply chain, and predicting future conditions are all aided by sales forecasting.

No wonder, forecasting sales consumes a large portion of the sales team’s time and energy. Despite the countless hours spent on this, the process churns out sub-optimal outcomes.

The traditional forecasting method conducted an in-depth historical analysis to arrive at a decision.

The modern pipeline technique assigns a percentage likelihood of a deal closing to every sales opportunity that is then multiplied by the revenue value associated with that opportunity. Let me explain to you in detail.

For example: if a $40,000 deal is likely to be closed, it may be assigned a close rate of 20%, and hence, a value of $8,000. However, in reality, it is not necessary that the deal would culminate in $8,000. The methodology is highly faulty and overly optimistic.

Sales forecasting done traditionally.

Faulty forecasts can lead to stock issues such as under-stocking or over-stocking. That’s where artificial intelligence can make all the difference! An Aberdeen Group study states that companies with accurate sales forecasts are 7.3% more likely to hit quota, and 10% more likely to grow their revenue.

If you want to drive profits year-on-year, you should forecast the sales of your eCommerce business accurately with AI. And for that, here’s what you should know:

  1. Maximize CLTV (Customer Life Time Value)

It is no surprise that acquiring a new customer is five times more expensive than retaining an existing customer. Many eCommerce businesses struggle to sustain the quality of products or services offered and match up to the customer’s specific requirements.

76% of customers believe it is easier to switch brands until they find an experience that matches their expectations, according to a Salesforce report. Unfortunately, 33% of businesses are poor at tracking customer journeys.

Therefore, the sales teams need to keep tabs on customer experience. AI can help in providing real-time insights into customer pain-points, sentiments, behaviors, and other buying triggers that can be handy from a sales point of view.

Alternatively, AI is also handy in identifying the customers who have previously bought from a brand before - thus, opening avenues to up-selling and cross-selling opportunities. When the sales teams have the right information, they can tap on that opportunity by delivering a personalized message, which would have not been possible earlier.

Read more about this topic here – “How to Predict Customer Churn Rate Using AI in eCommerce”.

  1. Enhance lead scoring

Frequently, the sales team makes lead scoring decisions based on faulty buying signals, which could be based on gut impulses or inaccurate information.

A DemandGen study states that although 68% of the B2B sales team implement lead scoring strategies, only 40% believe they add value.

You see - sales are easily affected by short-term trends in user preferences, price changes, promotional activities and seasonal events. That means each of these factors has to be taken into account when predicting sales.

AI algorithms can scan large volumes of real-time and historical data, it can identify the most lucrative sales leads. Those insights are helpful to sales teams for determining the fate of sales opportunities more accurately.

AI also takes into consideration all types of factors - including firmographic, demographic, and technographic data points.

Click here to know more about “4 Strategies for eCommerce Websites to Build Predictable Revenues”.

  1. Higher retention rates

Existing customers are 50% more likely to try a new product from you and spend 31% more as compared to new customers. The bottom line is: customer retention plays a massive role in driving the profitability of a business.

Retaining existing customers is easier than finding new ones.

Enter AI-driven chatbots. 90% of businesses state can resolve complaints faster with chatbots. 57% of companies agree that chatbots ensure a higher ROI with little effort. 53% of businesses identify chatbots as a “customer-first culture” creation tool.

An Oracle research states that 8 out of 10 businesses have already jumped the AI bandwagon or are planning to deploy the technologies for ramping up their customer service game. So, what’s stopping you?

Chatbots, irrespective of business size or sector, offers a platform to engage with the customers regularly and respond to queries. Artificial intelligence helps you monitor the customer activity patterns and proactively identify issues before they switch to a competitor.

AI-powered sales forecasting method gathers data about previously lost and won deals. It collects other data signals such as emails, phone calls, meetings, and analyzes how they affect the sales outcomes. It also collects information between the chatbot and potential customers.

These data points are then applied to the current pipeline, which gives insights into the next course of action.

This article talks about “How to Retain Customers in eCommerce Using Artificial Intelligence”.

  1. Improved close rates

CSO Insights states that only less than 50% of all forecasted sales opportunities prove to be accurate. With the help of AI, it is possible to serve insights about the individual in the client business who are most likely to usher the deals through to the finish line.

AI technologies can study pools of data and identify key purchase influencers that are not necessarily visible on the organizational charts of the client business. These insights can facilitate one-on-one conversations between the sales team and the personnel in question - leading to shorter sales cycles.

Click here to know more about “How AI Helps in Predicting Customer Churn in eCommerce”.

Summing up

Since the global eCommerce is on the rise, with the online sales projected to approach $5 trillion by 2021, and the US online retail sales predicted to exceed $740 bn in 2023, it is safe to conclude that eCommerce businesses have a lot to look forward to.

AI is transforming the domain rather rapidly. Besides empowering the online stores to forecast their future sales accurately and efficiently, it will undoubtedly streamline the operations the technology offers.

So what are you waiting for?

Leverage the full potential of AI with Datoin, and gain reliable sales forecasts for your eCommerce business. Contact us to implement AI technologies in your business today. After all - the value of a sales forecast is greatly influenced by its accuracy!

 

 

Tags: ecommerce retention metrics, sales forecasting, sales forecasting using artificial intelligence, AI for sales forecasting, customer lifetime value, lead scoring, artificial intelligence for ecommerce

About Datoin

For online businesses, E-Commerce startups Datoin is the best AI platform. Datoin is no code AI platform for business users who understand the domain and are not from tech or data science background. Datoin is designed with a vision that the online businesses of any size need not invest in building data science expertise to begin monetizing the insights from their own data to drive more sales.

Datoin looks at building a community of ECommerce startups, online subscription businesses  using advanced AI signals to sell productively.

ROI Centric Use cases:

  • Product recommendations, Engine 
  • Customer churn prediction
  • Predictive pricing
  • Dynamics discounting
  • Demand forecasting
  • Predicting List of Upsell/ Cross-sell ready customers 

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