Integration with PriceOptimizer Shopify app is seamless and only takes a couple of minutes. PriceOptimizer needs to integrate with your Shopify shop (to access sale date) and with your Google Analytics account (to access visitor data).
Install Shopify app
Installing PriceOptimizer Shopify app is easy. Just login to priceoptimizer.com dashboard, go to Settings page and click Install Shopify app.
Authorize Google Analytics
After you authorize Shopify PriceOptimizer app, you can authorize Google Analytics PriceOptimizer app. Simply go to Settings page and click Authorize Google Analytics. Please make sure that you are logged in the correct Google Analytics account for your Shopify shop web property.
After PriceOptimizer Google Analytics app is authorized, select and save the View ID for your Shopify e-shop property.
Editing cost of goods
Shopify does not natively support entering cost of goods for products in the Shopify platform. Since many features of PriceOptimizer require cost of goods for sales, these can be edited in PriceOptimizer dashboard in the Manage cost page.
Cost of goods (cogs) can be uploaded for products in a simple text file, where cost of goods is provided for each product variant.
Uploading cost of goods can be done in three steps.
- Download a product/cost of goods file - This file is exported from PriceOptimizer and contains all product variants with their corresponding cost of goods value (default cost of goods value is zero if no import was done yet)
- Edit cost of goods file - Edit actual cost of goods value for all product variants in the file from the previous step
- Update - Upload the updated cost of goods file to PriceOptimizer
After you import costs of goods for your product variants, you can also view the uploaded costs of goods in the table in the Manage cost page.
Setting new cost of goods for historical data
Imported cost of goods are used in PriceOptimizer statistics from the moment they are imported. However, the historical sales might still be associated with zero cost of goods.
If you wish to set your uploaded cost of goods for historical data as well, you can perform this action in the Overwrite cost of historical sales section by clicking on the Update button.
Available in Enterprise edition. Please contact us to obtain the full API specs and access.
With our secure API, you can integrate any custom e-shop platform with PriceOptimizer. API is used to sync daily sale and visitor data, and to automatically fetch latest price recommendations for any product.
The API is easy to use and you can use it to augment and improve your standard pricing based on statistics. You can fetch the optimal price for a product maximizing your selected metric, and based on the recommendation you can tweak your usual price.
PriceOptimizer learns from data to move the price based on historical conversions, and you can automate this process for your product collections. You can fetch optimized price recommendations for thousands of products daily.
You can chose between various optimization strategies.
- optimize profit - You want to maximize profit when selling
- optimize profit while still keeping sales - You want to maximize profit, while not losing sales
We can also provide custom reports and setup specific pricing strategy implementation, evaluation and benchmarking. Please get in touch with us to learn more.
Single product optimization
Single product pricing analytics are available in the Profit analytics page in PriceOptimizer dashboard.
Price performance for a product is displayed after entering a time range and cost of goods. You can compare different result metrics:
- Profit per visit - profit computed using your entered cost of goods and number of visitors for given price
- Revenue per visit - total revenue per visitor counting sales with given price
- Sales per visit - computed using total number of sales and number of visitors for given price
Price point with best (highest) metric conversion value is marked as Best price for optimizing *metric*.
You can also view statistical significance of your product date range results. Statistical significance measures the chance that obtained conversions are not due to luck or other factors.
Collection price optimization
After selecting a collection or a single product, you can select two date range periods and compare conversion performance in these two time periods. You can test different pricing strategies and compare the results of a strategy for sale performance.
After selecting two collections or products and a date range for a comparison you can compare conversion performance of chosen collections. For a selected time period, you can analyze and compare conversion performance of various product collections.
For example, you can examine your seasonal pricing strategies for two product collections and see the impact of pricing on the total margins (normalized per visit).
You can manage your product collections the Collections page in PriceOptimizer dashboard.
- Create collection - by uploading a text file containing a public product id on each line
- Delete collection - delete existing collection
Collection can be created by uploading a text file with public product id's (one per line).
For Shopify shops, text file should contain product variant id's.
|Best price for optimizing *metric*||Price with highest conversion for a given metric (profit, revenue or total sales).|
|Conversion||Number of sales (or total profit or revenue) divided by number of relevant visitors.|
|Cost of goods||Unit product cost.|
|Margin||Result of subtracting cost of goods from the selling price. Margin can be expressed simply as a monetary value or as % of the selling price.|
|Markup||What you're left with after subtracting cost of goods from the selling price, expressed as a % of the cost of goods price.|
|Profit per visit||Profit computed using your entered cost of goods and number of visitors for given price. Also known as profit conversion.|
|Revenue per visit||Total revenue per visitor counting sales with given price. Also known as revenue conversion.|
|Sales per visit||Computed using total number of sales and number of visitors for given price. Also known as sale conversion.|
|Statistical confidence||Measures how confidently we can believe, that observed conversions are not due to luck, as opposed to being caused by the controlled parameter. Technically, statistical confidence is 100*(1-p value).|