Keeping Prices Low With The Power Of Data

Data collection is enabling companies to implement a real-time dynamic pricing strategy, as well as staying competitive as far as ‘bundles’ are concerned while simultaneously monitoring third-party vendors
Keeping Prices Low With The Power Of Data
Nadav Roiter - Bright Data content manager and writer
Nadav Roiter | Data Collection Expert
06-Oct-2021
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In this article we will be discussing how businesses are implementing a real-time dynamic pricing strategy based on a use-case specific basis:

eCommerce 

Companies doing both back and front-end utilize data collection in order to stay competitive. 

Front-end eCom businesses, for example, monitor the web for:

  • Pricing within their niche, category or of a specific product or brand.  So for example if your business pertains to baby cribs in general or a specific brand of cribs then you could monitor what prices your competitors are offering those products for in real-time, and have your systems change pricing on your sites, and stores automatically. 
  • Bundles, meaning you could check what offers competitors are making. So, using the same example, a competitor’s crib may be the same price as yours but they are offering it with a free mattress and sheets and that could make their offer more competitive to would-be buyers. Once you have that information, you can adjust your bundle offering as well. 
  • Reviews,  i.e. collecting customer reviews on products that you and your competitors sell which can very often be translated into real terms of how to boost sales. For example a customer may write that the price does not justify what they received and then you can ‘sweeten the deal’ with a free gift or lower your pricing. 

Back-end businesses collect these same datasets. The main difference is that they do this across products and industries in order to feed the tools and dashboards that they offer as a service to digital business owners. For example, a company may offer a tool that allows store owners to input any product and see live competitor pricing. What is driving this on the back-end is a proxy network comprised of real-peer devices which offers accurate, geo-specific pricing from a consumer perspective.

Travel 

When it comes to travel there are also front and back-end options for companies, but the data collection principles are the same as with eCom which is why I will mainly discuss front-end, just keep in mind that everything I write applies to both. 

Many Online Travel Agencies (OTAs), flight comparison sites, apartment rental platforms, and the like are all leveraging user IPs to collect:

  • Pricing – In this instance businesses are collecting the price of flights, and hotel rooms as well as tours and other tourist excursions/attractions. When that information is fed back into their algorithms, sites are able to offer travelers the most competitive deals in real-time. 
  • Bundles – As with eCom, many times tourists prefer ‘travel deals’, including flight, accommodations, and a car rental. This is especially common with ski vacations where consumers prefer having their flight, accommodations, ski pass and even skin instructor sessions in an all-in-one package. By monitoring the web, competing companies can see what other sites are included in their bundles, and at what price. 
  • Search trends – Most modern customers begin their journey on a search engine which is why it is important to see what the current search trends are. For, example, a skier may be searching for ‘cheapest ski travel deals to Austria’. When you are privy to these trends you can tailor offers, pricing, and even blog content to appeal to these audiences. 

Brand protection 

Typically brand protection is viewed as ensuring no other entity is infringing on your Intellectual Property (IP) which is true. But beyond this, there is another common brand protection use case which is sometimes overlooked, monitoring the web for third-party retailer activity. This is especially true for large brands whose products are being sold by smaller vendors across the web. In order to ensure uniformity, and maintain their brand’s value, and integrity, they collect:

  • Pricing – Just as with physical retail in which case there is usually a ‘recommended retail price’ printed on an item’s packaging. So too, with digital retail, many wholesalers have a price that they do not want retailers to deviate from. By monitoring the web for specific items, brands can identify these inconsistencies and have their legal team reach out and request that a given vendor follow protocol.
  • Item description –  This is also true in terms of how an item is listed. If a brand’s merchandise is being misrepresented on a listing then this can actually dilute a brand’s value in the eye’s of their consumer base. By monitoring for specific brands, items and negatively correlating keywords, this can be avoided. 

Market research

Market research has many aspects. Data collection can help shed light on what is going on in a specific market before a new product line or application is launched, enabling changes to be made beforehand. These datasets commonly include:

  • Pricing – How are competitors pricing their Software as Service (SaaS)? Do they have a ‘Freemium’ pricing strategy? Will a ‘market penetration’ pricing approach be the right way to go when introducing a service to a new audience? Data is helping to answer these questions. 
  • User interaction – How are users interacting with a new application, for example? Are they downloading it and then uninstalling it because they thought it was free but everything within the interface costs money? These types of questions can have light shed on them when a data-first approach is applied, and can help iron out kinks in the rolling out of new services. 

As mentioned previously, most modern customer journeys begin with a search query. Many businesses are aware of which is why they pay search engines to appear at the top of search results for relevant keywords. Companies that are aware of the importance of being competitive in terms of search are monitoring for the following data sets on an ongoing basis:

Paid search results – Many businesses are happy to collect data on the keywords that competitors are paying to promote their products on search engines with. The reasoning behind this is that these are typically the most high-value, high-converting search terms. That means that yes, it is harder and more expensive to compete for eyeballs in that space. But it also saves companies a lot of time and leg work in terms of where customer interest currently is. The copy of these offers or listings is also very important because very often it will include a competitive price and/or words that pertain to pricing. For example, ‘the cheapest computer assistant on the market – starting at $29.99/month’. 

Organic search trends and queries – These are also very important as they show where consumer interest is now in real-time. As I mentioned in a recent article pertaining to the beauty industry:

“60% of the top search results on search engines for queries pertaining to beauty products are for content outlets that do not retail products.”

This essentially means that organic search trends are a gold mine for companies that want to find keywords that are relevant to their target audience, and have excellent, previously untapped monetization opportunities. 

The bottom line 

Data collection technology powered by a sophisticated network of real peers is serving as the basis for many businesses that are looking to be competitive on their digital outlets. Data collection is not only enabling smart/dynamic pricing strategies, but also more sophisticated approaches such as bundle arrangements, keyword monetization, and third-party retailer verification.  

Nadav Roiter - Bright Data content manager and writer
Nadav Roiter | Data Collection Expert

Nadav Roiter is a data collection expert at Bright Data. Formerly the Marketing Manager at Subivi eCommerce CRM and Head of Digital Content at Novarize audience intelligence, he now dedicates his time to bringing businesses closer to their goals through the collection of big data.

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