As an online retailer, most probably your goal is to attract customers, boost sales, ensure they are satisfied, and make sure they keep coming back. And this is what keeps you ahead of your competitors.
To curb this, online retailers are adapting their digital transformation to accommodate AI-based solutions to offer unique shopping experiences to the customers. Data analytics is being utilized in the online retail stores to switch from a broad-based marketing strategy to an effective alternative that’s tailored to keep every shopper hooked to your brand.
Predictive analytics tools can offer valuable insights for retailers to understand their customers based on digital footprint and behavior, thereby helping them to be innovative and covert more customers to boost sales.
But that’s not it. Let’s help you understand how predictive analytics will fit into various aspects of your business and benefit you.
1. Boost Sales with Personalized Recommendations
Do you know?
- 91% of consumers are more likely to shop with brands that provide relevant offers and recommendations (source).
- 80% of customers are more likely to purchase a product or service from a brand that provides personalized experiences (source).
- 72% of consumers in 2019 only engage with marketing messages that are customized to their specific interests.
No wonder, predictive analytics’ personalized recommendations are a big boost to your business, but not just attracting more sales but increasing the number of loyal customers.
Using cumulative data, predictive analytics brings you insights into the buying behavior of your customers. Based on this, it generates appropriate recommendations, suggesting AI solutions for retail that would add value to the existing retail experience of the customers.
a. Up-Sell Recommendations
Retailers can increase the package size and a roll-on promotion for specific items at attractive prices. For instance, “Save x% by buying the package” is a great example of this strategy. Most up-sell recommendations are tied to a specific SKU and offer related products along with the key ones.
b. Cross-Sell Recommendations
While upsell recommendations offer an expensive alternative to the chosen one, cross-selling recommendations show the popular products that can add value to the bought item.
Your customers will see the notifications saying, “People who bought this, also bought…”
c. Next-Sell Recommendations
These recommendations are defines after the customer has bought something. Thye might receive it as a thank-you letter or letter of confirmation of purchase by email. These recommendations are personalized for each customer, considering each information about them, and not just the last thing they have purchased.
2. Make Informed Decisions with Predictive Forecasting
Predictive forecasting is a technique that allows for continuous forecast adjustments to identify opportunities and risks to minimize losses and grow profitably. It uses historical data to predict future outcomes. For example, a sales manager can use predictive forecasting to create projections for sales revenue for the upcoming financial year or quarter.
It takes into account various parameters such as values, trends, cycles, sales, economic indicators, customer searches, and demographic data and/ or fluctuations to derive vital information. Businesses can benefit from this data-driven approach and aid the planning process.
Predictive forecasting takes into account different values, trends, cycles and/or fluctuations in your data to make predictions. This is a powerful data-driven approach that can be leveraged to aid your planning process.
But that’s not it. With predictive forecasting, online retailers can also predict and deliver up to the online shopper’s expectations even before they start searching over the internet.
3. Make Your Marketing More Strategic and Profitable
Predictive analytics can help eCommerce brands to determine customer behavior and shopping patterns. This enables them to direct their marketing efforts more effectively and strategically while understanding the key influencers of customer purchase decisions.
With AI-based solutions, you can fill in the gap and identify the required products and the products that are outdated. Studying consumer behavior also helps marketers to market their products in a way that is most impactful on consumers. Here’s a brief of how predictive analytics based marketing helps your business:
a. Understand Consumer Behavior
The insights from predictive analytics help marketers understand customer interests based on past interactions. Marketers can effectively segment the audience based on known interests and demographics. They can, therefore, serve individuals targeted messaging at the right time on the right device.
b. Optimize Resources and Spend
Marketers can analyze and know where to focus the ad spend based on valuable insights. Predictive data identifies the advertising channels and the right time frame that optimizes the ad spend and resources to reduce expenses and boost revenue.
c. Qualify and Prioritize Leads
Insights into customer behavior allow marketers to pinpoint the right audience segments closer to conversion. This data demonstrates how likely customers are supposed to act, allowing resources to direct attention to those consumers, minimizing wasted hours.
4. Ensure Best Customer Experience to Keep Them Happy
As retailers go above and beyond to nurture more relevant and meaningful customer relationships, predictive analytics help them create a customer experience that suits their distinct tastes. Predictive analytics can:
- Forecast customer need and what products could meet their needs to service them with relevant promotions
- Suggest products based on customer behavior and buying decisions
- Analyze customers’ spending habits and usage patterns to evaluate upselling and cross-selling opportunities
- Identify most effective product bundles, marketing content, communication channels, and timings
- Deliver instant gratification to customers through personalized suggestions and recommendations
- Determine the likelihood of customer termination and suggest actions to limit customer churn
With these insights in hand, online services can benefit by:
- Suggesting products with the maximum likelihood of buying
- Detecting unhappy customers and make changes accordingly
- Personalizing promotional material
5. Prevent Fraud
Offering the best products and exceptional services is no more enough for online businesses. They must offer cutting-edge security to their customers in order to grow.
Online fraud has been causing huge revenue losses and mars the reputation of businesses, thereby not just leading to huge traffic loss but even customers’ trust. To overcome this, eCommerce businesses can invest in AI-based solutions to track and identify suspicious behavior online.
Different shipping, and billing addresses, large value orders, using multiple modes of payment for the same shipping address, and international orders can be some indicators of suspicious behaviors.
Also Read- Top Data Analytics Business Ideas of 2023
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