Overview

This Sample Solution provides all required resources to deploy to the AWS cloud a fully functional SP-API application that implements the Price adjustment automation workflows guide end-to-end. Use this application to test the proposed solution, do changes and/or integrate it to your own product.

Sample Video Tutorial

Solution

This Sample Solution implements a re-pricing workflow that reacts to incoming ANY_OFFER_CHANGED and PRICING_HEALTH notifications calculating a new competitive price for the related selling partner's SKUs in order to achieve featured offer eligibility. If the new calculated price is above the minimum threshold defined by the selling partner, the solution executes a price change.

The solution consists of the following components:

A Step Functions state machine with a fully functional re-pricing workflow
Lambda functions that support each of the steps of the state machine
An SQS queue to receive ANY_OFFER_CHANGED and PRICING_HEALTH notifications
A DynamoDB table to store re-pricing rules for the selling partner's SKUs
A Secrets Manager secret to securely store SP-API app credentials

Workflow

The application waits for incoming SP-API ANY_OFFER_CHANGED or PRICING_HEALTH notifications. These events are processed by the SPAPIProcessNotificationLambdaFunction, which starts a Step Functions state machine execution with the re-pricing logic.

The state machine retrieves from the database all the selling partner's SKUs associated to the ASIN of the notification. Next, each SKU is processed individually. If not present in the notification payload, the SPAPIFetchPriceLambdaFunction retrieves additional pricing information for the SKU using the Product Pricing API. The SPAPICalculateNewPriceLambdaFunction calculates a new competitive price using the price change rule specified for the SKU in the database. The supported rules are "FIXED" for a fixed deduction to the featured offer price (e.g. featured offer price - $0.01), "PERCENTAGE" for a percentage deduction to the featured offer price (e.g. featured offer price - 5%) and UseCompetitivePrice a bool value which when set as true, reprice the item using the competitivePriceThreshold value from PRICING_HEALTH notification when available. Finally, if the new calculated price is above the specified minimum threshold, the SPAPISubmitPriceLambdaFunction submits the price change using the Listings Items API.

Pre-requisites

The pre-requisites for deploying the Sample Solution App to the AWS cloud are:

Registering as a developer for SP-API, and registering an SP-API application
An IAM user with permissions to create a new user, a policy, and attach it to the user
- If you don't have one, you can create it following the steps under Usage - 2. Configure Sample Solution App's IAM user
The AWS CLI
- If not present, it will be installed as part of the deployment script
The Python app requires the following packages: boto3, requests, and setuptools. If not present, they will be installed as part of the deployment script
GitBash
- in case you use Windows in order to run the deployment script.

Usage

1. Update config file

To allow the Sample Solution App to connect to SP-API, the config file has to be updated to match the set-up of your SP-API application.

Open app.config file and replace all occurrences of <dev_value> following the instructions below:
Update ClientId and ClientSecret attribute values with Client Id and Client Secret of the SP-API application respectively
Update RefreshToken attribute value with the refresh token of the selling partner you will be using for testing
Update RegionCode attribute value with the region of the selling partner you will be using for testing. Valid values are NA, EU, FE for production usage or NA_SANDBOX, EU_SANDBOX and FE_SANDBOX for Sandbox testing.

Note: While updating the config file, don't leave blank spaces before and after =, and don't use quotation marks

Sample config file:

ClientId=amzn1.application-oa2-client.abc123def456xyz789
ClientSecret=amzn1.oa2-cs.v1.abc123def456xyz789
RefreshToken=Atzr|Abc123def456xyz789
RegionCode=NA_SANDBOX

2. Configure Sample Solution App's IAM user

I. Create IAM user

In order to execute the deployment script, an IAM user with IAMFullAccess permissions is needed. To create a new IAM user with required permissions, follow the steps below. If you already have a user with IAMFullAccess policy, you can skip to Configure IAM user credentials section

Open the AWS console
Navigate to IAM Users console
Click Add users
Select a name for your user
In the Set permissions page, select Attach policies directly
In the Permissions policies, search for IAMFullAccess. Check the policy, and click Next
Review the changes and click Create user

II. Retrieve IAM user credentials

Security credentials for the IAM user will be requested during the deployment script execution. To create a new access key pair, follow the steps below. If you already have valid access key and secret access key, you can skip this section.

Open the AWS console
Navigate to IAM Users console
Select your IAM user, which has IAMFullAccess permissions
Go to Security credentials tab
Under Access keys, click Create access key
In Access key best practices & alternatives page, select Command Line Interface (CLI)
Acknowledge the recommendations, and click Next
Click Create access key
Copy Access key and Secret access key. This is the only time that these keys can be viewed or downloaded, and you will need them while executing the deployment script
Click Done

3. Execute the deployment script

The deployment script will create a Sample Solution App in the AWS cloud. To execute the deployment script, follow the steps below.

Identify the deployment script for the programming language you want for your Sample Solution App.
1. For example, for the Python application the file is app/scripts/python/python-app.sh
Execute the script from your terminal or Git Bash
1. For example, to execute the Python deployment script in a Unix-based system or using Git Bash, run bash python-app.sh
Wait for the CloudFormation stack creation to finish
1. Navigate to CloudFormation console
2. Wait for the stack named sp-api-app-<language>-random_suffix to show status CREATE_COMPLETE

4. Test the sample solution

The deployment script creates a Sample Solution App in the AWS cloud. The solution consists of a Step Functions state machine with a fully functional workflow. To test the sample solution, follow the steps below.

Open the AWS console
Navigate to DynamoDB items console
Under Tables, select the table created by the deployment script, named SPAPISellerItemsTable-random_suffix
Select Create new item and add the following attributes with the corresponding value:
1. ASIN (Type String): The ASIN that you will use for testing
2. SKU (Type String): The SKU that you will use for testing
3. SellerId (Type String): The id of the seller that you will use for testing
4. MarketplaceId (Type String): The id of the marketplace that you will use for testing
5. Condition (Type String): The condition of the item that you will use for testing. Valid values: new, used (for Python) or New, Used (for Java)
6. IsFulfilledByAmazon (Type Boolean): true if the item that you will use for testing is fulfilled by Amazon, false otherwise
7. PriceChangeRule (Type String): The price change rule of the SKU. Valid values: FIXED, PERCENTAGE
8. PriceChangeRuleAmount (Type Number): The price change rule amount. This amount will be related to the price change rule chosen in step 7. For example, if the PriceChangeRuleAmount is set to 10, it could be interpreted as 10 USD or 10% depending on the value of the PriceChangeRule.
9. MinThreshold (Type Number): The minimum monetary list price for the SKU. Example: 10 (= 10 USD/EUR)
10. UseCompetitivePrice (Type Bool): To accept the usage of useCompetitivePrice rule from PRICING_HEATH notification. To understand more about this attribute check Pricing FAQs

To test in sandbox environment, add the following item into DynamoDB:

In the Create Item page select JSON view on the right side, copy and paste the item below and click in create item.

{"ASIN":{"S":"B00V5DG6IQ"},"SKU":{"S":"NABetaASINB00V5DG6IQ"},"Condition":{"S":"new"},"IsFulfilledByAmazon":{"BOOL":false},"MarketplaceId":{"S":"ATVPDKIKX0DER"},"MinThreshold":{"N":"5"},"PriceChangeRule":{"S":"FIXED"},"PriceChangeRuleAmount":{"N":"1"},"SellerId":{"S":"AXXXXXXX"},"UseCompetitivePrice":{"BOOL":true}}

Navigate to SQS console
Select the SQS queue created by the deployment script, named sp-api-notifications-queue-random_suffix
Select Send and receive messages
Under Message body, insert the following simplified notification body. To test the ANY_OFFER_CHANGED notification, use the following message in the SQS queue:

If you want to test with production data, replace all attributes with the real values for ASIN, SellerId and MarketplaceId.

{
  "EventTime": "2023-07-31T20:41:15.002Z",
  "PayloadVersion": "1.0",
  "NotificationType": "ANY_OFFER_CHANGED",
  "NotificationVersion": "1.0",
  "Payload": {
    "AnyOfferChangedNotification": {
      "SellerId": "AMY6FKRUBY7XV",
      "OfferChangeTrigger": {
        "MarketplaceId": "ATVPDKIKX0DER",
        "ASIN": "B00V5DG6IQ",
        "ItemCondition": "new",
        "TimeOfOfferChange": "2023-07-31T20:40:53.101Z",
        "OfferChangeType": "Internal"
      },
      "Summary": {
        "BuyBoxPrices": [
          {
            "Condition": "New",
            "LandedPrice": {
              "Amount": 10.00,
              "CurrencyCode": "USD"
            },
            "ListingPrice": {
              "Amount": 9.00,
              "CurrencyCode": "USD"
            },
            "Shipping": {
              "Amount": 1.00,
              "CurrencyCode": "USD"
            }
          }
        ]
      },
      "Offers": [
        {
          "SellerId": "AMY6FKRUBY7XV",
          "SubCondition": "new",
          "ListingPrice": {
            "Amount": 20.00,
            "CurrencyCode": "USD"
          },
          "Shipping": {
            "Amount": 1.00,
            "CurrencyCode": "USD"
          },
          "ShipsFrom": {
            "Country": "US",
            "State": "WA"
          },
          "IsFulfilledByAmazon": false,
          "IsBuyBoxWinner": false
        }
      ]
    }
  }
}

To test the PRICING_HEALTH notification, use the following message for sandbox testing or change sellerId, asin and marketplaceId to test in production:

{
  "notificationVersion": "1.0",
  "notificationType": "PRICING_HEALTH",
  "payloadVersion": "1.0",
  "eventTime": "2020-09-23T21:30:13.713Z",
  "payload":
  {
    "issueType": "BuyBoxDisqualification",
    "sellerId": "AMY6FKRUBY7XV",
    "offerChangeTrigger":
    {
      "marketplaceId": "ATVPDKIKX0DER",
      "asin": "B00V5DG6IQ",
      "itemCondition": "new",
      "timeOfOfferChange": "2020-09-23T21:30:13.409Z"
    },
    "merchantOffer":
    {
      "condition": "new",
      "fulfillmentType": "MFN",
      "listingPrice":
      {
        "amount": 1200,
        "currencyCode": "USD"
      },
      "shipping":
      {
        "amount": 100,
        "currencyCode": "USD"
      },
      "landedPrice":
      {
        "amount": 1300,
        "currencyCode": "USD"
      },
      "points":
      {
        "pointsNumber": 0
      }
    },
    "summary":
    {
      "numberOfOffers": [
        {
          "condition": "new",
          "fulfillmentType": "MFN",
          "offerCount": 3
        }
      ],
      "buyBoxEligibleOffers": [
        {
          "condition": "new",
          "fulfillmentType": "MFN",
          "offerCount": 3
        }
      ],
      "buyBoxPrices": [
        {
          "condition": "new",
          "listingPrice":
          {
            "amount": 900,
            "currencyCode": "USD"
          },
          "shipping":
          {
            "amount": 100,
            "currencyCode": "USD"
          },
          "landedPrice":
          {
            "amount": 1000,
            "currencyCode": "USD"
          },
          "points":
          {
            "pointsNumber": 0
          }
        }
      ],
      "referencePrice":
      {
        "averageSellingPrice":
        {
          "amount": 1050,
          "currencyCode": "USD"
        },
        "competitivePriceThreshold":
        {
          "amount": 980,
          "currencyCode": "USD"
        },
        "msrpPrice":
        {
          "amount": 1300,
          "currencyCode": "USD"
        },
        "retailOfferPrice":
        {
          "amount": 1000,
          "currencyCode": "USD"
        }
      }
    }
  }
}

Click Send message
Navigate to Step Functions console
Select the state machine created by the deployment script, named SPAPIStateMachine-random_suffix
Under Executions, you will see a workflow for the notification submitted through SQS
To check the workflow status and navigate into the individual steps, select the workflow and use the Graph view and Step Detail panels

5. Extra

The deployment script also creates a Lambda function that subscribes selling partners to notifications. You can integrate this function to your product to easily onboard to the notifications feature. To test the function, follow the steps below.

Open the AWS console
Navigate to Lambda console
Select the notification subscriber function, named SPAPISubscribeNotifications-random_suffix
Select Test tab
Under Event JSON, insert the following payload. Replace RefreshToken, RegionCode and NotificationType with the corresponding values of the selling partner and notification type you want to subscribe to.
```
{
    "NotificationType": "PRICING_HEALTH",
    "RegionCode": "NA|EU|FE",
    "RefreshToken": "Atzr|Iw..."
}
```
Click Test
The function will return destination Id and subscription Id

6. Clean-up

The deployment script creates a number of resources in the AWS cloud which you might want to delete after testing the solution. To clean up these resources, follow the steps below.

Identify the clean-up script for the programming language of the Sample Solution App deployed to the AWS cloud.
1. For example, for the Python application the file is app/scripts/python/python-app-clean.sh
Execute the script from your terminal or Git Bash
1. For example, to execute the Python clean-up script in a Unix-based system or using Git Bash, run bash python-app-clean.sh

7. Troubleshooting

If the state machine execution fails, follow the steps below to identify the root-cause and retry the workflow

Navigate to Step Functions console
Select the state machine created by the deployment script, named SPAPIStateMachine-random_suffix
Under Executions, you can use the Status column to identify failed executions
To troubleshoot errors, select the corresponding workflow execution and use the Graph view and Step Detail panels
After fixing the issues that caused the error, retry the workflow by clicking on New execution. The original input parameters will be automatically populated
Click Start execution, and validate the results

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DEPLOYMENT.md

DEPLOYMENT.md

Overview

Sample Video Tutorial

Solution

Workflow

Pre-requisites

Usage

1. Update config file

Sample config file:

2. Configure Sample Solution App's IAM user

I. Create IAM user

II. Retrieve IAM user credentials

3. Execute the deployment script

4. Test the sample solution

5. Extra

6. Clean-up

7. Troubleshooting

Files

DEPLOYMENT.md

Latest commit

History

DEPLOYMENT.md

File metadata and controls

Overview

Sample Video Tutorial

Solution

Workflow

Pre-requisites

Usage

1. Update config file

Sample config file:

2. Configure Sample Solution App's IAM user

I. Create IAM user

II. Retrieve IAM user credentials

3. Execute the deployment script

4. Test the sample solution

5. Extra

6. Clean-up

7. Troubleshooting