The global retail scenario is evolving at a rapid pace. When we saw brick-and-mortar sales gradually decreasing from 2013 to 2018, the industry was going through a change of landscape due to the growth of the digital commerce industry- or the e-commerce industry.
By 2026, the global retail industry is estimated to grow up to $5.4 trillion. With this boom, it is of utmost importance that the e-commerce industry designs optimized products, programs (campaigns), and pricing strategies.
While designing strategies for appropriate pricing, product assortment, and campaign management may look like two different activities, they are all directed to the same objective- to provide the best experience to their customers. All three activities can also help an e-commerce firm design the best pricing strategies for its customers. However, it is key that the firm has the required data to conduct all the mentioned analyses and design the required recommendations.
Pricing is one of the pivotal horizontal in most industries that results in a direct correlation with revenue and profits. A lot of firms spend a huge amount of resources on finding the best pricing strategy. Most of these ways to decide the best price for a service or a commodity are driven by data. We will study the various aspects of pricing in the e-commerce industry and how it depends on data.
Price as a powerful strategic tool
Let us look at how pricing has become the most powerful strategic tool in any industry.
For any business, the most important performance metric is ROI or Return on Investment. This metric is often calculated using the formula given below:
ROI = (earnings from the investment (in desired currency)- the cost of investment (same currency as earnings))/ cost of investment
Now, we see that the key factors in the calculation of ROI are the earnings and the costs associated with any investment. It is thus necessary to study these elements in your business. For any retail brand, there are four main strategic points:
Price: An optimal price point considers production costs, supply chain costs, the target customer, time of sale, overall demand, and product attributes. It forms the earnings part of the ROI.
Product: A good product portfolio considers the type of products and other attributes like brands and scales and tries to optimize that to meet the customers' demand. It contributes to the cost aspect of the ROI.
Promotion: Promotions or discount campaigns are designed as a cost to the firm to provide the customer with incentives to buy the product. This again adds to the costs of the ROI.
Place: A place in the e-commerce industry is defined as the distribution channel, the design, and the presence of the website and mobile applications across platforms and devices. This contributes to the cost factor in the ROI.
As we see above, among the 4 P's, price is the only major factor that contributes to earnings. The other three are cost factors. Hence, pricing becomes a very significant strategic tool that can help e-commerce firms maximize their revenue. It can also help them maximize profits when decided appropriately.
Since the online retail industry does not have a physical interaction with its customer, it largely depends on data to capture these trends in the behavior and purchase patterns. This data-driven pricing strategy is key to the success of the e-commerce industry.
Data-driven Pricing Strategies are key for the e-commerce industry
While the most common way of pricing products is by determining the demand for the same, a lot of new sophisticated techniques have been devised to price products and services effectively across industries. A good number of industries have already adopted these techniques. We want to study the intricacies of pricing in the e-commerce industry. Price is a strategic tool to control all the performance metrics of your business, directly and indirectly. It basically alters your sales (revenue), margins, profits, and even your market share.
In the e-commerce industry, pricing is more dynamic than in brick-and-mortar stores. This is because of the fast-paced nature of the environment and the complex behavior of the customer. To design an appropriate pricing strategy, you can use and analyze data about your products, customers, and campaigns. You can also design personalized pricing recommendations for your customers on the basis of their activities so far.
Since you can track and store historical data points on a digital retail site, it becomes both necessary and convenient to use this to predict the effect of your pricing strategies. The insights from this study can be then fed into the design of your future pricing strategies. All these nuances and more make pricing a delicate metric.
Like all other industries, pricing in e-commerce has to be optimized to maximize sales (revenue) and margins.
An optimal price point is achieved when there is a balance between supply and demand. (highlight this statement)
At this exact price, a consumer has the maximum probability of buying your product. If the price is too high, the product most likely won’t sell- or the sales or revenue will be low. On the other hand, if the price is too low, you may lose the potential margin. If a consumer's spending capacity for a particular product is $100, pricing the product at $90 is a missed opportunity and loss of margin.
While this is a straightforward concept, finding this optimal point in the e-commerce industry becomes tricky-often due to the dynamic nature of the environment. To add to the complexity, there are multiple e-commerce sites that compete against each other. It is often difficult, if not impossible, to track the pricing strategies of your competitor.
Additionally, the customer and the retail store do not have a direct interaction which makes it difficult to study the customers' sentiments directly. You then have to design feedback forms or use the customers' journey through your site as a proxy for their sentiment. Tools and techniques like web scraping can help you overcome these hurdles and provide the required data for the appropriate analysis.
Due to the dynamic nature of the e-commerce stores and customers, it is vital that actions and recommendations are designed on a real-time basis. This basically means one has to deal with high velocity and high volume data. Since a lot of customers will be active on a particular site, doing multiple things simultaneously, it is necessary to capture all these data points and analyze them to get actionable insights.
For instance, if multiple customers are browsing the products on your website and a fraction of them complete the transaction and a few of them just add products to the cart and compare prices of multiple products from multiple sources, you need to capture these trends to the best of your ability. Capturing this data will not only help you understand your customers better but will also help you optimize your product assortment and pricing strategies accordingly.
Pricing Strategies in the e-Commerce Industry
Setting an optimal price, as discussed above, depends on a lot of factors. It is not a straightforward process. You need to consider factors like the product attributes, customer sentiment towards the product, promotions being run for the product category, general demand of the product and even costs involved, time of sale, distribution channel, etc. There are several strategies that are analyzed and employed while pricing a product, a few of which are listed below:
Studying demand-price elasticity
Pricing of product bundles
Pricing on the basis of discounts and promotions
Customized Pricing for customers
The cost-based approach of Pricing
Let us look at these approaches in detail.
1. Price-demand elasticity
Price demand elasticity determines a direct relationship between the demand of the product and its price. It is defined as the rate of change of demand per unit change in price. The mathematical formula for the same is:
Price Elasticity= (Δquantity/quantity)/(Δprice/price)
In other words, if a small change in the price of the product leads to a large change in its demand (sales), the product is highly elastic- or its demand is highly susceptible to price changes.
On the other hand, if a significant change in the price of the product leads to little or no change in its demand, the product is inelastic. Some products, by their nature, are inelastic.
For instance, bread is a staple commodity, and despite the change in its price, the demand will always be high and stable. This is because consumers will always require bread and will have a high purchase capacity for bread. Bread is hence, an inelastic product.
Thus for inelastic products, retailers can play around with the prices in a huge bracket and experiment with the prices without much effect on its sales. However, it is key to note that even for inelastic products, there are external factors like competitor prices that limit the range within which the prices can be tweaked. For elastic products however, you need to estimate the break-even point where you get the optimal revenue without affecting the demand (in units) significantly.
2. Pricing governed by product offerings
The products offered largely decide the price point associated with them. Factors like brands and sizes of products are direct factors that affect the price. For instance, if the product is manufactured and offered by an established brand, it will be priced higher than a locally-sourced unbranded variant of the same product.
All e-commerce firms first benchmark their prices on the basis of these product attributes- often specific to the product category. For instance, in the category of fruit and vegetable products- attributes like fresh produce, canned products, sugar-free versions, and other variants determine the price benchmarks.
Similarly, in products like travel accessories, size (large, small and medium) plays an important role in benchmarking the price of the products. An illustrative table has shown mentioned below:
Online retail stores also have the option of studying the customers' sentiments from the reviews and comments posted for a particular product. The prices of these products can then be altered accordingly to either increase revenue or the margin. However, there are some complex nuances in retail, more so in the online retail industry, that make pricing a complicated strategy. One of them is cross-selling, up-selling, and bundling of products.
Suppose a customer is browsing for large-sized travel suitcases; it might be possible that he would also require a duffel bag or a smaller bag. Designing a recommendation engine that suggests options for smaller bags would be an intelligent decision for every e-commerce site.
We see recommendations on most e-commerce sites like: "Customers who bought product X also bought the following products." or "Customers like you have also bought the following products." These recommendations use historical data from purchase patterns of similar customers or the trends associated with certain products. They tap into the customer behavior of buying associated products and create a real demand for certain products by magnifying the latent need.
Once this demand has been created, the next step is to price the associated products or product bundles appropriately. The combined price of the large suitcase and the smaller bag is often lower than the direct sum of their individual prices.
The purchase of a suitcase and a duffle bag together leads to a 41% reduction in price compared to the cumulative price of both items bought separately.
3. Pricing governed by promotions and discounts
Promotions and discounts are a significant part of a customer's online shopping journey. Every e-commerce site is filled with promotions around the year. They might be available site-wide or on particular products. These promotions provide customers with incentives to shop from a particular site, thus increasing the footfall on the site and effectively the sales. This cost factor often helps retailers benchmark prices accordingly.
Retailers consider a lot of factors while rolling a campaign out. You need to consider the time of the year, target audience, products covered under the campaign, and even competitor promotions and prices before designing a campaign. Special events like festivals, sports events, and educational seasons are often targeted for designing campaigns.
The key metrics to measure the promotional effectiveness of a brand are:
Promotional frequency: How often a specific unit or set of units belonging to a given brand goes on sale/offer
Promotional timings: When a specific unit or set of units belonging to a brand tend to go on sale/offer
Promotional depth: The level of promotional discount for a specific unit or set of units in percentage (e.g., “50% off”) or absolute monetary (e.g., “Save 1 dollar”) terms
These promotions, if spaced correctly, can help a brand earn maximum revenue while establishing its market share. A lot of online retailers also have long campaigns for 2-3 days that offer discounts of varying depths across different product categories.
4. Customized Pricing for Customers
If you monitor your customers' purchase trends and their association with your brand, you can design customized pricing recommendations for them. A lot of e-commerce sites offer discounts to loyal customers- often known as 'premium' customers. They also track the customers' affinity towards a product and offer them plans to subscribe to the product at a regular interval- say monthly. This subscription plan offers these products at discounted rates to these target customers.
Customer value is key to all B2C businesses. Online retail is no exception. A lot of e-commerce sites roll out customized pricing plans to a few customers and often use strategies like A/B testing to measure the effectiveness of the plan before rolling it out to other customers.
5. Cost-based approach for Pricing
The costs associated with a product is often the key factor used to price the same. There are several costs associated with a product- procurement costs, manufacturing costs, supply-chain costs etc. Let us consider all these costs clubbed into one metric, 'Cost' for simplicity of estimation. The margin is the earning of the seller when sold to a customer. The relationship between cost, price and margin can be defined as follows:
Price= Cost + Margin
Another metric, 'price floor,' indicates the lowest price that a product can be sold at. This relationship can help you price products using the concept of break-even points. The break-even point is the number of units to be sold to compensate in the loss of earnings due to a decrease in price.
In other words, the break-even point is high when the price is low. The break-even point decreases as the prices increase. However, the 'price floor' indicates the lowest a product can be priced at. The below table illustrates the same.
6. Dynamic Pricing
E-commerce sites have the liberty to price their offerings dynamically. These prices can change over the course of the day or even for varying customers, among other factors.
Also known as 'smart pricing' or 'real-time pricing, this is an automated pricing method that allows online retailers to update their prices according to factors like demand and price competition. This concept uses the idea of estimating price demand elasticity to arrive at a price point. For instance, if the demand for a particular product keeps increasing over a period of time, the sellers can safely increase the price. This will help them maximize the revenue while the demand is increasing.
You can also use dynamic pricing against competitor prices. You can evaluate the prices offered by your customers on a real-time basis and use these comparisons to tweak the prices offered by you.
Amazon’s revenue growth from 2004 to 2018
Amazon is one of the largest retailers that employs dynamic pricing regularly. It is observed that Amazon changes its prices every 10 minutes on average. The online retailer saw a 27.2% increase in revenue from 2012 to 2013 and generated close to 232 billion U.S. dollars in 2018. Amazon has been one of the top 10 retailers constantly.
7. Competitor-based pricing
In this highly competitive industry that is driven by data, competitive price benchmarking is a significant tool. It uses data on the prices offered by competitors to give you pricing recommendations. It is a customer's tendency to compare the prices offered by various sellers for a given product. Therefore, you’ll lose customers if your prices are significantly higher than your competitors' pricing points.
To offer the best price, it becomes necessary to constantly monitor the competitor prices and tweak your offerings dynamically. This would require you to scrape the prices mentioned on your competitors' sites and design a descriptive-analytical model that gives you pricing recommendations on the basis of these comparisons. Web scraping can be a valuable tool in the field of competitor-based pricing.
It is important to note that competitor price analysis is not limited to price point comparisons for the same product. It can also be used to compare the type of promotions being rolled out to the customers, the diversity of the product assortment, and hidden costs like shipping costs or packing charges.
How can Web Data Scraping help Pricing in e-Commerce?
Web data extraction can play an important role in designing a pricing strategy for the e-commerce industry. It can help you make data-driven decisions that are significantly more effective than heuristic decisions. Let us look at a few ways in which web data extraction solutions can help pricing:
1. Records and analyze pricing, price changes, and promotion
Online retailers can use web scraping to extract real-time latest information on product offerings, promotions, campaigns, and pricing changes by online retailers around the world to inform pricing and promotional strategies. Using consumer sentiment data in the form of unstructured comments, social media activity, and grievances can help you identify what products to sell, what services to offer, and how to improve your online strategy.
2. Gain a competitive edge
E-commerce sites can monitor gaps in competition through continuous tracking of competitors’ pricing and product assortment, along with online promotions by country and category on a regular basis. You can use this data to tweak your product offerings as well.
3. Plan for future innovation and new product development
E-commerce can study market trends, customer sentiment, and reports from innovation and development departments to monitor and predict innovation in the industry. You can use it to track product descriptions to help your R&D and product development strategies. You can use data like ingredients, packaging and variants/ fragrances online, product positioning (claims, warnings, and features), and pricing (changes and markdowns) to identify new opportunities.
4. Study your own e-commerce growth
Track your own e-commerce presence and digital-route-to-market strategy. You can monitor your customers' clicks, views, and conversions to identify the scope of improvement for your retail strategy. This can help you identify successful strategies for online product assortment, product positioning/descriptions, pricing, and website presence to sell your products in the most efficient manner.
Most e-commerce sites place very high importance on pricing analytics. Pricing analytics helps them design a strong online strategy for maximizing their revenue. It helps them draw their customers and establish brand value in the market.
E-commerce sites are finding new sources of real-time data and insights. These sources are also rapidly evolving with the continuing development of online and in-store analytics. Most firms deal with a huge variety of data — the company’s prices and promotions, competitors’ prices, product availability, and economic and seasonal conditions, among others. They use this data to drive analytics in their organization and then use the insights to create actionable recommendations.
The effectiveness of these measures depends on two key metrics- Accuracy of the insights drawn and the research expertise of the company. It is necessary that the data extracted from various sources are vetted for accuracy. Additionally, the efficiency of the analytical tools also should be monitored and optimized. The insights can then be safely used to design recommendations. Furthermore, the analytical team of e-commerce firms should know what data to deal with and where to find answers to their questions. Conducting a wrong analysis for a given problem statement could be a grave mistake.
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