Learn how e-commerce owners can leverage data assets to become more profitable and retain customers in the long run by using Decision Intelligence (DI).
A webshop is just one of the first steps towards building a profitable online business and every online retailer wants to outperform their competition. By using Decision Intelligence (DI), e-commerce owners can leverage data assets to become more profitable and retain customers in the long run .
The golden rule of the general trading world also applies to e-commerce: spending less and selling more maximizes profit. However, there are many factors that can influence an online retailer’s profit margin. Forward-thinking decisions regarding merchandise procurement, inventory levels, pricing and attracting top customers are all key considerations for online retailers and every single step along this workflow involves the production and collection of vast amounts of data.
It can be relatively easy to collect this data, but the trick is to make the best use of it to improve your sales performance. To handle these huge amounts of data manually will most likely result in you losing a lot of valuable time and missing the big picture.
The use of Decision Intelligence in e-commerce, on the other hand, quickly takes into account each of the components that influence each other and helps to maximize profit margins and/or generate more sales, depending on your needs.
DI is a strategic management tool that helps you to make smarter decisions based on emerging Artificial Intelligence (AI) technology. This enables company decision-making processes to be accelerated and optimized by collecting all relevant data, analyzing and comparing it and evaluating the results to derive trade-offs and recommended courses of action.
These results either initiate a completely automated process or give the company decision-makers logical suggestions to be given the opportunity to include human experience and consideration in their assessment of the situation. Thanks to DI, both of these types of far-reaching strategic decisions and tactical course changes can be made more quickly and efficiently than ever before. DI helps to boost business success at various levels.
Online business is fiercely competitive where the war on price is fought over margins. It’s the maintenance, or preferably the increase, of profitability that is by far the most important segment in need of support from DI. With DI tools, online retailers can use their sales and customer data to:
Customers are not always just looking for bargains, there are those who actually look to spend money to purchase high-quality and expensive products and these are particularly valuable for any e-commerce company. It is estimated that 20% of customers generate around 80% of sales.
It’s relatively straightforward to classify your customers based on frequency of use and purchase volume by using one-dimensional customer segmentation (e.g., ABC analysis). However, the use of DI enables refined, multivariate customer segmentation on the basis of many variables, so that different groups of customers can be analyzed even more precisely and targeted and addressed more effectively.
This involves subdividing customers in line with their demographic, geographic and psychographic data and taking into consideration their buying motives and the way they interact with the brand. The result is an accurate overview of customer segments. There is good profit potential from both types of customers, those who generate high sales with just a few orders and those who stand out with smaller shopping baskets but a high order frequency.
Based on the resulting analysis, it is then possible to customize specific marketing measures where the offer of high-margin products reaches potential buyers in a targeted manner.
Customers can compare which store offers the lowest prices with just a few clicks when purchasing online and this makes pricing one of the most important competitive tools for any online retailer. By using manual price adjustments it is practically impossible to react quickly or efficiently enough to any fluctuations, so this is where one of DI’s core competencies comes in: dynamic pricing.
Putting your prices on autopilot increases customer growth whilst maximizing your profit margins. Prices can be automatically adjusted within a matter of minutes to changing circumstances and conditions. Based on market changes, seasons and even the time of day, online retailers can offer their customers the right products at the right time.
In e-commerce, Decision Intelligence tools offer the unrivaled advantage of dynamic pricing where both revenue and sales volume can be increased by offering customers competitive prices without reducing profit margins. Smart price management can even make it possible to increase margins when applying discount prices.
Companies tend to want to avoid discounting, as under normal circumstances this usually reduces profit margin. However, there are a variety of situations that justify or even require the use of discounts:
It is essential to plan any intended discount campaigns with the expected outcome in mind. Should a hard-to-sell item be offered as part of a bundle at deep discount? Which bestselling product needs just a small discount to be pushed for a short term? How can both of these products be profitably bundled?
In e-commerce, Decision Intelligence uses data-based solutions to help identify efficient trade-offs for decisions about discount levels and product bundling. The AI-based self-learning set of algorithms developed by tech start-up paretos not only finds trade-offs between influencing factors much faster than other systems, it also generates far more optimal solutions. In this way, the paretos AI sets new benchmarks for data analysis.
So-called ‘event’ or ‘seasonal’ discounts are linked to specific dates (e.g., Valentine’s Day, Black Friday) or seasons (e.g., summer sales). Special discount days always attract huge amounts of shoppers, so online retailers can attract customers who are looking specifically for special offers by offering price reductions. Seasonal discounts can also help to reduce inventory (including out-dated products), but such hyped discount promotions tend to attract bargain hunters rather than loyal shoppers and margins could suffer.
The most effective way to avoid price markdowns and the associated reduction in margin is to improve inventory management. Planning the procurement of goods is an important tool for improving margins. Sales and inventory data help you to decide which products to stock and how much inventory to maintain so that customer demand can be met and overstocking can be prevented. In addition to this, buying seasonal inventory in advance can reduce its cost of sales and increase profit margin.
DI proves to be particularly effective for identifying patterns necessary for predictive merchandise procurement. Inventory and supply chain data is used to optimize inventory decisions and reduce tied-up capital. With data-based analytics, AI technology can be used to make sophisticated forecasts for the optimal procurement of goods.
Inventory procurement is one of the biggest challenges of fast-growing e-commerce companies that want to generate growth. High stock levels require massive investment, whilst too little inventory leads to one of the riskiest situations for retaining customer loyalty: stock-out. If products are out of stock, online retailers have to set their inventory in the store to “0” or “availability on reorder”, which is likely to lead to customer churn and a drop in sales. This situation must be avoided at all costs.
To combat this, e-commerce retailers can use Decision Intelligence tools to optimize inventory levels with demand forecasting models. These are data-based predictions of when there will be increased or decreased demand and for which product, and this enables an informed decision on inventory volume which in turn allows inventory costs to be optimized. Stock levels can even be categorized by margin, sales and product turnover through inventory optimization. Similarly, DI can be used to monitor the impact of an inventory management system on margins.
Nowadays, creating connections between related products in the online store is an integral part of the digital shopping experience. “Customers who bought this item were also interested in this” – and the customer is prompted to buy more products. The same applies to the recommendation of related or logically connected products during checkout.
Upselling (displaying a higher-value product version) and cross-selling (displaying complementary products) are two of the most proven tactics for increasing sales but there is one difference between them: upselling usually leads to customers choosing a higher-margin product, while cross-selling doesn’t always drive higher margins, but increases the average order value by adding more products.
Using buying patterns, Decision Intelligence can help online retailers to identify the best opportunities for upselling and cross-selling. This helps predict when customers will buy certain offers and recommends upgrades for products or services.
Every offer is only as good as its marketing. Online retailers also face the challenge of using their marketing budget efficiently to achieve their sales and profit goals. The possibilities are as broad as the channels, including paid social marketing, Facebook, Instagram, TikTok and influencers.
The decisive factor here is not just any available financial resources but, above all, the goals you want to achieve. Do you want to launch an image campaign to make the brand more widely known? Do you want to reach more customers, introduce a new product line or increase sales?
When it comes to building a successful e-commerce business, Decision Intelligence is the best tool for deciding where to start for which goal and with which budget. DI can help optimize ROAS, the most important metric for most online marketers, by providing recommendations for the marketing mix.
Lifetime value (LTV) is the total income generated by a customer throughout their interaction with a particular brand or company. The longer a customer remains loyal to the company and continues to buy, the greater the LTV. Acquiring a new customer is five times more expensive than retaining an existing customer, so DI is a valuable aid to help to increase their LTV.
To achieve this, DI tools use data history to identify high-performing customer segments and suggest customized marketing campaigns and personalized offers to encourage customers to buy high-margin products. Customer loyalty works best through personalized approaches but the real challenge is to contact customers at the right time with the right offers.
DI enables all customer data from various sources to be analyzed more quickly to obtain a complex picture and to find the offer strategy that is precisely tailored to the respective group of customers.
Would you like to know if paretos is the right solution for you? Feel free to schedule a non-binding consultation appointment.
Paretos is the leading AI-based Decision Intelligence software for optimized decision-making processes. With paretos, businesses can identify, plan, execute, and track business potentials through automated processes across the entire organization.
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