How Competitor Prices Affect Conversion Rates and User Behavior
Does competition affect sales? If you think ’no’, perhaps you’ve never been through a bustling market on a busy day :)
Some questions, however, don’t have easy answers. For example:
- Why is there an increase in the CPA in already existing display advertising campaigns for a particular product category, e.g., smartphones? What if prices on the website don’t reflect current market conditions?
- Which products to choose for an email promo campaign? What prices for most popular products do shoppers consider the best value?
- Why did sales go down? What is the reason: prices not reflecting the market, or a decrease in website traffic? How does the deviation from the market price affect the number of product views?
- What price to put in order to achieve strategic sales objectives? What does the price elasticity curve look like in this particular product category?
These questions can only be answered by comparing your prices to the prices of your competitors and having the complete data about customer behavior. In this article, we address the advantages of monitoring your market competition, and explore how you can start tracking competitors’ prices. We will also take a close look at a few reports, providing useful information for your business.
According to PwC, 60% of customers choose a particular store because they believe it offers reasonable prices. Not low. Reasonable. This suggests that pricing strategy affects not only the store’s revenue, but also customer loyalty.
To understand how competitors’ prices affect conversion rates and user behavior on your website, you need to analyze the following data:
- Customer touchpoints on the website (channels, sessions).
- Competitors’ prices (price, time, promo, availability).
- Transactions from the CRM (orders, margins, product catalog).
In order to ensure the reliability of analysis, it’s important not only to collect the data, but also to piece it together in one system. To do that, we used the following services:
- Google BigQuery — to store large amounts of data.
- OWOX BI Pipeline — to send user behavior data from Google Analytics to Google
- Competera Competitive Data — to collect data about competitors’ prices.
Now let’s explore, step by step, how you can obtain the necessary information and how to use it.
1. Collect data in Google BigQuery
The first thing you need to do is to collect statistics about product card views. For this purpose, you need to implement the Universal Analytics Enhanced Ecommerce plugin on your website. For more information on how to do this, read our blogpost.
Next, set up competitive price monitoring using Competera. Specify the scanning frequency and upload the list of products you want to monitor. We recommend that you set the scanning frequency to “every day”, in order to ensure the maximum reliability of the data.
We recommend that you use Google BigQuery to store and process the data. Google BigQuery is a secure service with simple pricing and high processing speed. In addition, it has integrations and ready-made libraries for uploading data from various CRM systems (this will be useful if you’re collecting information about your competitors yourself). Another advantage Google BigQuery has over other services is its scalability — you can upload any amount of data you need.
User behavior data from Google Analytics can be sent to Google BigQuery using OWOX BI Pipeline. With OWOX BI Pipeline, you can:
- Export raw non-aggregated data. This enables better data-driven decisions based on the more complete data.
- Access data in real time. This gives a huge advantage, as it’s important to know what prices were there on your competitors’ websites at the very moment a user was viewing your website’s product card and making a purchase decision.
- Collect unsampled data down to a hit. This helps obtain full information about the behavior of your website visitors, as even small websites often generate more than 50,000 rows per day.
More information about OWOX BI Pipeline, in comparison with Google BigQuery Export for Analytics 360, can be found in our blogpost.
The data about competitors’ prices can be imported from Competera to Google BigQuery with the readily available OWOX BI Pipeline integration. Visit our Help Center for detailed information on the data structure and setting up the pipeline.
In general, you can use any other price monitoring software to collect data about prices. The main thing is to adhere to the minimally required data structure:
||RECORD||NULLABLE||Product data from your website|
||STRING||NULLABLE||Product ID on the website|
||RECORD||NULLABLE||Data about competitors|
||STRING||NULLABLE||Name of the competitor|
||RECORD||NULLABLE||Scan data for the competitor's website|
||TIMESTAMP||NULLABLE||Scan time on the competitor's website|
The data about transactions, margins, and the product catalog, can be uploaded from the CRM into Google BigQuery using any of the client libraries.
2. Merge data from different tables
Now as data is collected in Google BigQuery, product card views and competitor prices still are stored in different tables. It’s necessary to put this data together, which can be easily done by using JOIN clauses.
The data structure for reports should look like the following:
||TIMESTAMP||Product view date|
||STRING||Unique ID of the user (Google Analytics)|
||STRING||Product ID on the website|
||FLOAT||Product price on the website at the time of viewing|
||TIMESTAMP||Product card view time|
||FLOAT||Revenue by product|
||INTEGER||Number of purchases|
||FLOAT||Product price on the competitor's website|
||TIMESTAMP||Scan time on the competitor's website|
||STRING||Name of the competitor|
This table can be complemented with other data, depending on your hypothesis and what you want to test.
3. Process the data and build reports
After you’ve collected all the necessary data, you can process it in Google BigQuery with SQL queries and then send the results to Google Sheets using the OWOX BigQuery Reports Addon. Let’s take a closer look at two reports you can get as a result.
The first report demonstrates the effect price deviation from your competitors prices has on the conversion rate on your website. Let’s say you want to improve conversion rates for a certain product category, e.g., video cameras, by offering a discount. What discount should you set in order not to face a decrease in gross margin and not to lose customers’ confidence? To determine this, use the following chart:
The horizontal axis shows the percentage of price deviation from the market conditions, and the vertical axis shows the conversion rate. The size of the circle indicates the amount of revenue. Should the need be, it’s also possible to build such a curve not only for a particular product category, but also for a particular vendor or advertising channel.
In our case, the report demonstrates that products cheaper than the market predictably have higher conversion rates. How do discounts affect conversion rates and revenue? The green circle indicates that the most revenue is obtained by selling products at a market price. However, products sold at a price 5% cheaper than the market have a higher conversion rate, as indicated by the pink circle. Products sold at a price 30% cheaper than the market have the highest conversion rate, but bring the least revenue. It can be concluded that the optimal discount for this particular product category is 5%. It wouldn’t be cost-beneficial to put another discount.
Another interesting conclusion drawn from this report is that if you sell products much cheaper than the market price, you lose the customers’ confidence. Look at the orange circle: with a 25% discount, the conversion rate has dropped to 0.9%. Of course, product category matters: shoppers are ready to buy cheap books, while cheap appliances and cosmetics make people suspicious.
Let’s look at the other report. Take for example, you want to evaluate customers’ confidence in your store and find out which product categories, at what prices, are bought best.
Use a table demonstrating how the price deviation from the current market conditions affects sales in different product categories:
This particular example demonstrates that shoppers perceive the store as a trusted retailer of laptops, smartphones and tablets — customers buy them at prices higher than the market. At the same time, the maximum revenue is generated by laptops sold 5% cheaper than the market. Perhaps, it’s worth launching more advertising campaigns with this proposal.
The following report will help you find out where your most loyal customers are coming from:
The chart above demonstrates the revenue generated through different advertising campaigns. Colors indicate the percentage of price deviation from the market prices. In our example, the campaign number 2 brings the most customers ready to pay above the market price, while the campaign number 6 brings the least. A similar chart can be built for other metrics, for example, margins.
This information will help you choose the best campaign for promoting your products. Please note that with different product margins, campaigns might have the same ROAS with different revenue. You’ll be able to increase revenue by reaching a wider audience via the paid channels that are most likely to bring you potential buyers.
By monitoring and analyzing competitors’ prices, marketers and category managers will be able to:
- Improve revenue, turnover and marginality by updating prices in each category with account of sales and competitors’ prices.
- Improve strategic performance indicators. For example, increase the conversion rate for a certain product by offering an optimal discount.
- Manage pricing, with consideration of advertising campaigns and traffic sources. Find out which channels and campaigns bring you the most loyal customers, and target your advertising efforts to these particular channels.
We have prepared a file with SQL queries and a detailed guide on how to create the reports described in this article. There are queries for both the data collected using BigQuery Export for Analytics, and the data collected using OWOX BI Pipeline. Enter your email to get the guide delivered to your inbox. To see more useful reports based on the data about competitors’ prices, watch the webinar put on by Competera and OWOX BI specialists.
Do you monitor pricing competition? If yes, how do apply the results? We’re looking forward to your comments :)