Home Business Business Efficiency at Lower Costs: 5 Best-Working Steps for Digital Retailers

Business Efficiency at Lower Costs: 5 Best-Working Steps for Digital Retailers

by Olufisayo
Best-Working Steps for Digital Retailers

Retailers are closing down brick-and-mortars, the supply chain cycle is undermined, and competition is getting tougher. 2020 has turned out to be a tough year, right? But don’t forget a good old saying that the crisis always brings opportunities. Believe it or not, the post-COVID economy gives digital retailers a plethora of such opportunities.

To gain an advantage out of the recent trends in e-commerce, the business must invest in transformation and advanced tech solutions powered by artificial intelligence and machine learning. But how can a retailer invest in technology when all the resources are spent on sustaining current operational flow and overcoming the pandemic’s devastating consequences? Well, the first step is cost optimization.

As the price remains a crucial communication point between the retailer and customer, the pricing policy becomes the major domain that is worth being optimized. Price optimization brings business the real money almost immediately. So, let’s look at the most effective and proven means of improving pricing efficiency while lowering the costs.

1. Define your online positioning

As dozens of new retailers start selling online, the competition in e-commerce is getting tougher. Earlier on, digital retailers could have been quite successful even without a distinct price positioning, but things are different now.

Roughly speaking, there are three major types of positioning in digital retail. The first model implies selling all types of products for all types of customers. Choosing this type of positioning means selling at low margins but with a high turnover rate. Marketplaces are a perfect example of such an approach.

The second model is, probably, the most commonly used across the e-commerce segment. It implies giving the best offering for a particular limited group of products. It means the shoppers can’t buy everything at your store, but some of the products you offer are available at the best price.

Finally, the third type of positioning is based on the exclusive range of assortment, i.e. the seller offers unique or luxury products that are not easy to find across the market. This model is less dependent on pricing compared to the first two types.

The clear determination of your positioning is essential to choose and optimize pricing tools. For example, you might need to monitor competitors’ prices if you’re selling at the marketplace or claim to guarantee the best price. In contrast, for exclusive range stores, price monitoring plays a less significant role.

2. Automate pricing process

Regardless of the positioning model you choose, pricing automation is a mandatory step for all retailers willing to spend less money on pricing while making it more efficient. Most of the digital retailers have already automated some of the processes linked to pricings. For example, you can hardly find a company making price monitoring manually.

But automating only particular elements of the pricing process is hardly a sustainable approach. Moreover, it may contribute to financial inefficacy as there is always a risk of a human mistake while interpreting the automatically collected data and making the pricing decisions. What retailers need instead is a comprehensive, integrated, and coherent pricing automation.

The question is how to get there without allocating considerable investments. The automated pricing decision trees might become a good solution. Using such decision trees, retailers can automate the entire pricing process based on custom logic, any type of variables, or rules. What it means is that the risk of human mistake is mitigated while the efficiency increases and repricing time is significantly reduced.

pricing decision tree example

A pricing decision tree example

If some real-life examples of such automated pricing systems work better for you, the case of the renowned sporting goods retailers Wiggle might help. The company managed to cut repricing time by 50 percent, increase its competitive coverage, and switch to more complex pricing rules in only a few months.

3. Split competitors across different product groups

Now, regardless of your price positioning model, there are definitely particular products in your portfolio that should be priced in regard to the competition. In most cases, these are the KVI positions and Best Price Guarantee (BPG) products. To price this kind of SKUs competitively, you must keep tracking the fresh and relevant market data. And price monitoring is a crucial tool to make sure your price positioning against the competitors is sustained correctly.

One of the major challenges retailers faced recently is the drastic increase in price monitoring costs. To a large extent, this process is a result of the post-COVID boom in digital retail. As more and more players move online, the retailers are forced to monitor more data points which, eventually, means pricing costs increase. 

So, how can the business reduce the price monitoring costs without compromising on its quality? The first advice is to split competitors across different product groups. The point here is that you never compete with every competitor in every product group. In other words, if you compete with a competitor ‘A’ with products ‘D’ and ‘C’, while competitor ‘B’ is likely to steal the sales of your ‘E’ and ‘F’ products, then there is no point to monitor competitor ‘B’ prices for products similar to ‘D’ and ‘C’ and vice versa.

To put it simply, splitting competitors across different product groups helps to optimize the number of data points for monitoring by means of cutting the unnecessary ones. Here is a numerical example: if you have 1000 products and 50 competitors in total, you’d have to monitor 50000 data points. But, if you split 50 competitors into 10 product groups, you would only have to monitor only 10000 points.

4. Adjust the monitoring frequency depending on the product role

Another way to optimize pricing costs is to diversify the monitoring frequency based on the product role in a portfolio. How does it work? As you know, each SKU has a different role in a portfolio depending on the product’s lifecycle stage. The most common types of SKU involve:

  • First entry products
  • Exclusive range
  • Best Price Guarantee products (often the same SKUs serve as KVIs)
  • Cash generators
  • Revenue generators
  • Long-tail products
  • SKUs under promo or markdown

As a retailer, you might not have all types of SKUs available on the shelf. At the same time, it is also hardly possible to make business with only one or two types of products, especially taking into account that the SKU roles are not stable and may transform from time to time.

Now, the prices for various types of products change with different frequencies. For example, the long-tail products might be available at the same price for a month while for other SKUs, like Cash generators or BPGs, the price can change even a few times per day. What it means is that there is no point to monitor all products with the same frequency.

webinar on pricing costs optimization

Source: webinar on pricing costs optimization

Let’s look at an example: if you have the same 1000 products per 10 competitor groups and you monitor them each day for 30 days, you’d get 300000 data points in one month. Now, let’s divide this group into two: 800 long-tail products and 200 KVI positions.

If you’d monitor prices for 200 KVIs by 10 competitor groups 2 times per day, you’d get 120000 for a month. Monitoring prices for 800 long-tail SKUs 4 times per month gives another 32000 data points. In general, you get less than 200000 points instead of 300000 per month. This is how diversified monitoring frequency can save your money and increase effectiveness.

5. Monitor marketplaces/price comparison sites instead of direct competitor sites

The last advice for today will help you not only to reduce the costs of price monitoring but will also significantly increase the competitive coverage. Monitoring marketplaces instead of direct sites of competitors is something you should start doing right away.

Here is how it works: if you monitor 1000 products per 10 groups of competitors, you’d have to pay for 3000 data points per month. Now, if each competitor is represented on a particular marketplace (e.g. Google Shopping), the data for 10 groups would count as only 1 data point, i.e. the marketplace itself. What it means is that you’ll have to pay only for 300 data points instead of 3000. Sounds good, isn’t it?

Another ultimate advantage of monitoring marketplaces stems from the fact that it can help you to increase your competitive coverage as new players and potential competitors will be identified immediately after they start selling online.

As you see, there is always room for cost optimization even in the case of such essential processes as price monitoring. Eventually, fueling an automated pricing decision tree (like the one we’ve described earlier on) with the high-quality data points can itself boost your pricing efficacy and bring the business efficacy to the next level!


The boom of e-commerce following the CV-19 crisis intensified the competition in digital retail. Old and new market players have to implement advanced tech solutions to reinforce their market positions. At the same time, the crisis has also badly impacted the innovation budgets of the businesses.

Subsequently, in order to innovate, digital retailers must first reduce costs. In this regard, pricing monitoring costs optimization appears to be a perfect source for allocating extra funds.

Splitting competitors across different product groups, adjusting the monitoring frequency depending on the product role, and monitoring marketplaces instead of direct competitor sites are worth being considered first. Later on, the money allocated as a result of optimization could be reinvested in more advanced pricing solutions required for sustainable growth.

YuliaAbout the author

Yulia Beregovaya is a pricing expert with more than 10 years of professional background in Marketing Research and Analytics. Today, as a Pricing Solution Architect, Yulia is focused on helping the businesses to reach their targets through tech-driven pricing.

Featured Image Source: “Five Fifty”, an overview of retail and e-commerce trends by McKinsey

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