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RE-BUY: Product Suggestions on My Account Page

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Overview

The RE-BUY WPO is about offering personalized product recommendations for logged-in customer on your My Account page (and other pages only accessible for logged in customers).

If you are not familiar with WPOs, Customer Journey Steps, WPO Levels, Widgets, or Page layouts, please read the introduction: Widget & Page Optimizers (WPO)

Purpose

Cleverly chosen personalized recommendations in the "My Account" page for:

  • Re-order

  • Increase "Share of Wallet”

  • Assortment education

  • etc.

How should the widgets appear visually?

The RE-BUY widgets typically are displayed with a label (title) on top and a slider or product recommendations (with left and right arrows) as documented as “product slider” in the https://boxalino.atlassian.net/wiki/spaces/BPKB/pages/57671688/Check-list+empower+your+Website+Layout+with+Narratives#Layout-Blocks-(Templates)-Check-list. There might be several blocks on the page, one below each other, or in different sections of the page. However, you might go for much more advanced layouts as in this screen-shot.

Key focus: Customer Journey Personalization (CJP)

Personalization is important here because your start pages have a very broad context (on your home page, every product of your e-shop might be considered, while on a search or category page, only the product matching the search or the category are in context). Therefore, instead of “simply” showing your global top-sellers, current promotions, or novelties, you can instead (or in addition) select products matching the prior click and purchase behavior of each visitor individually. And as every visitor is always logged in on these pages, we recommend putting more focus (at least at first) on the Customer Journey Personalization (CJP).

Related WPOs

The RE-BUY WPO belongs to the LOYALTY customer journey step (fifth column of the diagram above) and corresponds to LEVEL 1 as it is solely about products and not other types of content: combine it with PROMOTE, READ to also support recommendations of other types of content like banners or blog articles and use it within a smart, personalized and dynamic layout with PRESENT.

What widgets should you consider?

One or several product recommendations blocks, each with a specific label, can be integrated into each selected page (My Account and other logged-in pages).

Each block can display the products in a slider or in a grid (the number of products per block is not limited but is typically less than 20). The number of blocks is also not limited and will be returned in a sequence by our API. Combine it with PRESENT to retrieve a dynamic personalized list of blocks embedded in a complete page layout (including other visual blocks for banners, information messages, emotional pictures, … all of which can be also personalized and A/B tested). As an example of such a case, here is a use case with Marketing Topics: Personalized Marketing Automation on Qualipet Homepage

WPO Optimization Strategies

The Widget strategy can be configured in the Widget Strategy Editor and supports all the standard Strategy Use-Cases.

Here is a selection from our Best Practice Strategies in 3 sections (what to configure before your go-live, what could be your first A/B test about and more advanced practices for later stages).

1. What to start with (for the go-live)?

Group

Name

Short description

1

Product & Content Statistics (PCS)

Smart Bestsellers

Best-selling trends, top recently generating revenue / margin products, often contributing to higher AOV, …

2

Product & Content Attributes (PCA)

Exclude Ineffective Products

Exclude Ineffective Product Groups

Remove out-of-stock products, as well as zero or low-value products, low margin, or any other unwanted products

(the second practice considers the 1st or 2nd most sold sku of each product group, for example to exclude products which top sold variant(s) are currently out of stock)

3

Product & Content Attributes (PCA)

Value Flags

Promote products or content with valuable value flags (5 stars, best-seller, novelties, recent discounts, staff pick of the week, …)

4

Visitor Journey Personalization (VJP)

Views > Product Attributes

Promote products or content with attribute values matching previously viewed products

5

Customer Journey Personalization (CJP)

Purchases > Product Attributes

Promote products or content with attribute values matching previously bought products

6

Customer Journey Personalization (CJP)

Exclude Recently Purchased Products

Exclude products the customer has recently purchased

7

Visitor Journey Personalization (VJP)

Exclude Products already in the basket

Exclude products that are already in the basket of the visitor

2. What could be a/b tested first?

All the elements of the “What to start with?” list could also be used in a/b testing. The list here-after provides additional Best Practices that can be quickly tried.

Group

Name

Short description

1

Product & Content Statistics (PCS)

Product Views & Engagement Trends

Most viewed or baskested items within different time frames

2

Visitor Journey Personalization (VJP)

Views > Price Range

Views > Higher Price Range

Products which match (or are slightly higher than) the products price range of the previsouly viewed products

3

Visitor Journey Personalization (VJP)

Views > End-up Buying

Products which are often bought in the same session after viewing the same products the current visitor has already viewed

4

Visitor Journey Personalization (VJP)

Views > Discovery Tags

Views > Defining Tags

Promote products or content with Discovery Tags matching previously viewed products.

Each product gets a list of Discovery Tags representing the most common search terms used to find a product.

Each product gets a list of Defining Tags representing which is a subset of the product attributes values that have been identified as important in the selection of a product

5

Customer Journey Personalization (CJP)

Purchases > Individual Collaborative Filtering

Neural Collaborative Filtering for individual recommendations based on the purchases of the customer and leveraging the patterns in the purchase behaviors of other customers

6

Product & Content Statistics (PCS)

Widget Display $Value Self-Learning

Promote products based on the self-learning of the Widget click/display score, either directly on the amount of clicks or on the conversion, average bought value or margin generated by the clicks

Display = visual impression detected on the screen of the user before, during and after scrolling on the page

7

Visitor Journey Personalization (VJP)

Basket > Often Bought Together

Basket > Collaborative Filtering Bought Together

Promote products often bought together with products already in the basket of the visitor

(first practice with statistics, second variant with AI Collaborative Filtering)

8

Visitor Journey Personalization (VJP)

Views > Often Bought Together

Views > Collaborative Filtering Bought Together

Promote products often bought together with products the visitor has already viewed

(first practice with statistics, second variant with AI Collaborative Filtering)

9

Visitor Journey Personalization (VJP)

Views > Often Viewed in Same Session

Views > Collaborative Filtering Viewed Same Session

Promote products often viewed in the same session as products the visitor has already viewed

(first practice with statistics, second variant with AI Collaborative Filtering)

10

Customer Journey Personalization (CJP)

Purchases > Rebuyable products

Promote products the customer has already bought which can be repurchased

Each product can be automatically labelled as repurchaseable if enough people bought it several time, or if it belongs to a category you know to be repurchasable or doesn’t belong to any category which you know to be not-repurchasable.

3. What else could be experimented with?

Expand the list to see all the additional Best Practices of this WPO.

 Other Best Practices

Group

Name

Short description

1

Marketing Alignment (MA)

Promoted Campaigns

Promote products or content in the target of active promoted campaigns

2

Visitor Journey Personalization (VJP)

Viewed Category, Brands & Landing Pages

Used Facets Values

Used Price Range

Used Higher Price Range

Previous Search(es)

Related Search(es)

Promote products matching the

  • viewed top product-listing pages (category pages, brand pages, campaign landing pages, …)

  • used facets values or price range (search / product listing filtering options)

  • slightly higher price range than previously used

  • prior searches (or related to the prior searches) of the visitor.

3

Customer Journey Personalization (CJP)

Last Purchase > Often Bought After

Last Purchase > Collaborative Filtering Bought After

Promote products often bought after the last purchase of the customer

(first practice with statistics, second variant with AI Collaborative Filtering)

4

Customer Journey Personalization (CJP)

Purchases > Often Bought By the Same Customer

Purchases > Collaborative Filtering Bought By the Same Customer

Promote products often bought by the same customer (based on the purchase history of the customer)

(first practice with statistics, second variant with AI Collaborative Filtering)

5

Visitor Journey Personalization (VJP)

Basket > Often Basketed Together

Basket > Collaborative Filtering Basketed Together

Promote products often basketed together with products already in the basket of the visitor

(first practice with statistics, second variant with AI Collaborative Filtering)

6

Visitor Journey Personalization (VJP)

Views > Low/High End

Promote products or content in the same Price Quadrant as previously viewed products.
Each product is connected to a price percentile according to its group (e.g.: category), lower percentiles (e.g.: <20%) are labeled Low-End while top percentiles (e.g.. >80%) are labeled High-End.

7

Customer Journey Personalization (CJP)

Purchases > Low/High End

Promote products or content in the same Price Quadrant as previously bought products.
Each product is connected to a price percentile according to its group (e.g.: category), lower percentiles (e.g.: <20%) are labeled Low-End while top percentiles (e.g.. >80%) are labeled High-End.

8

Customer Journey Personalization (CJP)

Purchases > Discovery Tags

Purchases > Defining Tags

Promote products or content with Discovery Tags matching previously bought products.

Each product gets a list of Discovery Tags representing the most common search terms used to find a product.

Each product gets a list of Defining Tags representing which is a subset of the product attributes values that have been identified as important in the selection of a product.

9

Customer Journey Personalization (CJP)

Wish-list > Products

Wish-list > Products Attributes

Wish-list > Products Discovery Tags

Wish-list > Products Defining Tags

Promote products

  • currently in the wish-list of the visitor

  • matching the values of attributes of products in the wish-list of the visitor

  • matching the Discovery/Defining Tags of products in the wish-list of the visitor

See Discovery and Defining Tags definition above

10

Visitor Journey Personalization (VJP)

Basket > Products Attributes

Basket > Products Discovery Tags

Basket > Products Defining Tags

Promote products

  • matching the values of attributes of products in the basket of the visitor

  • matching the Discovery/Defining Tags of products in the basket of the visitor

See Discovery and Defining Tags definition above

11

Visitor Journey Personalization (VJP)

Views > Smart Bestsellers on Clustering

Best-selling trends within the Cluster the visitor is predicted to belong based on his prior product views.

Customer Clustering distributes all customers into clusters based on their purchase history

12

Customer Journey Personalization (CJP)

Purchases > Smart Bestsellers on Clustering

Best-selling trends within the Cluster the customer belongs.

Customer Clustering distributes all customers into clusters based on their purchase history

Additional ideas for Widget Strategies

  • Request 4-5 highly specific blocks and only display the first 2-3 returning some recommendations

  • Change the label of your blocks depending on the content of the recommendations (e.g.: “Based on your last purchase” versus “From your most purchased brand”)

  • Segmented personalization (based on the customer demographic, cluster, etc.)

  • If your widget is labeled “bestseller”, consider setting up a FILTER with a minimum number of sales or with a bestseller label in the PCA - Value Flags Best Practice to avoid the risk that personalization starts showing products with lower sales levels

Onboarding project plan

Here are our suggestions for the project management steps of the RE-BUY widgets.

This process described how to integrate the RE-BUY WPO by itself without any other WPO combined. if you want to integrate the RE-BUY together with other WPOs, contact Boxalino to discuss an adequate project plan.

Task

Description

Comment

1

Pre-requisites

Make sure the Pre-requisites steps are completed and already deployed in production

  1. Data exports

  2. Tracker integration

Exports for products and transactions are required, as well as all the standard tracking events.

2

Pages

Define the pages where the RE-BUY widgets will be integrated

Example:

  • My Account Page

  • Other logged-in pages

3

Widgets

Define the RE-BUY widgets to be integrated on each page and where they should appear on the page (if you decide that some widgets should not appear for all visitors, define the logic deciding when they will appear or not)

Example names:

  • myaccount_recos

  • myaccount_bestsellers

  • myaccount_promotions

  • myaccount_novelties

4

Labels

Define the label of each of the RE-BUY widgets in each language (the title that appears on top of the product slider)

Examples:

  • Your personalized suggestions

  • For you

  • Bestsellers you might like

  • Promotions of products you already bought

  • Newcomers of brands you purchased

5

Integrate API + Configuration

Integrate Boxalino Narrative API and configure your widgets in the Boxalino Admin.

  1. Layout Blocks of the templates (typically 2 templates: product slider (container) and product (for each product display) as documented as “product slider” in the https://boxalino.atlassian.net/wiki/spaces/BPKB/pages/57671688/Check-list+empower+your+Website+Layout+with+Narratives#Layout-Blocks-(Templates)-Check-list

  2. Widgets with empty strategies in the RE-BUY WPO in Boxalino Admin with the exact names defined in step 3

  3. A narrative defining the layout of widgets (with positions if separated zones) referring to the names of the widgets as accessors and with the labels defined in step 4

As a result, you should be able to see the widgets appear in your dev/stage front-end showing valid products but without any relevant logic in the selection of the products.
If you display widgets in separated zones of the page, you can use different positions so the widgets are grouped by positions in the Narrative API response

6

Configure Widget Strategies

Define the strategy of each of the RE-BUY widgets (first in prose and then by configuring the widget in the Boxalino Admin)

Boxalino can support you for the configuration of the widget strategies

7

Test & Deploy

Testing in your dev/stage environment and go-live

In case you have a separate prod and a stage account, make sure to copy your configuration in production before going live

Integration notes

  • Pre-requisites: Data exports (products, transactions, and optionally customer data) and Boxalino Tracker integration.

  • Boxalino Narrative should be configured in Boxalino’s admin on the first appearing widget on the page (which should be the one called in the API request). The Narrative should define the layout of all the widgets (name of the widget to be indicated in the accessor parameter possibly with a hitCount to define how many products should be returned, for example: “topsellers[hitCount=15]”) as well as the labels.

  • Boxalino Narrative API will return a list of blocks (for each block of product recommendations) each with a list of sub-blocks (with the list of products) as documented here, (make sure to make only one call to our API to retrieve all widgets and not a call per widget which would cause poorer speed performance on your frontend)

  • The products returned will always include the product ids (which might be all you need) and other product fields can be returned as well if requested in the API calls (see Return Fields)

  • The request and the response should not be cached (consider an AJAX call in case you need to cache some parts of your page for performance reasons).

  • Make sure to tag your HTML with the required classes and entities returned by Boxalino as bx-attributes so the Boxalino tracker can identify automatically the scrolling behavior (including the appearance of the products when using the slider arrows).

  • Before going live, make sure to control the Tracker Checklist

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