Consumer Insights: Empowering Customer 360 and Precision Marketing with Data Intelligence

By Johnson Chiang, Solutions Architect

In the course of transformation to “New Retail”, companies in the e-commerce, entertainment, social games, music, and aviation industry are all desiring deep consumer-centric insights from data to drive a “Consumers-Goods-Stores” upgrade.

Consumer Insights is a new solution initiative that externalizes Alibaba’s data technology from its core retailing business. It supports your company to turn fragmented consumer data into an integral asset, do precision marketing upon customer preferences to retain customers, strengthen brand loyalty, and acquire new customers.

This article outlines how Consumer Insights works and how you should be thinking about using it in your own business.

What Is Consumer Insights?

Nowadays, we often see retailers and companies utilizing data technology to help marketing, IT, operations, and customer services, to deliver better user experiences across multiple channels. To address this concern, we believe the very first priority is to have a unified, holistic view at your consumers. However, we also see the following problems typically faced by both IT and business teams in an organization.

  1. Non-Universal and Non-Uniform Data: Consumer data is usually scattered in siloed organizations, from heterogeneous data sources such as CRM sales data and user behavior data. Moreover, online data is usually not utilized and integrated with offline data. Data is not connected, uniform, and integral to do further analysis.
  2. Operating and Marketing without Intelligence: Consumer analyses used to rely on BI team manual efforts to create descriptive report from SQL or CRM. These solutions are no capable of adapting to the dynamics of businesses and consumers’ ever-changing behavior.

Consumer Insights is a product powered with Alibaba’s retail domain know-how, and brings you the following key advantages:

  1. Builds your own universal consumer data model and One ID mapping by fully leveraging your data, from online to offline.
  2. Has a label factory to generate and manage “labels” and it allows you to customize labels, which can be predictive deep-mining attributes using machine learning algorithms.
  3. Draws crowd portraits of screened cluster and segments consumers to proceed precise interaction.

Now, with the single and holistic consumer profiling, your company is able to usher in dynamic new customer engagement models based on “insights” — not only market automation.

Use Cases

Consumer Insights is built for various business scenarios across BI, customer service, sales, marketing, commerce, or wherever your company is seeking for an integral insight:

360-degree Customer Analytics

This solution is applicable to the following scenarios:

  1. As a sales operation manager, you want to analyze consumer purchase behavior of your commodity.
  2. As a hotel owner, you want to give customer service staff a 360-degree view about the guest being checked in to provide personalized experiences.

Precision Marketing

This solution is applicable to the following scenarios:

  1. As a marketing manager, you want to perform activity planning, select the right customer group based on attributes, push ads to targeted customers to retain, wake, promotion, via the customer AIPL lifecycle, and have a tool to see the evaluation of conversion rate.
  2. As a customer service, you want to perform post-sales interaction within 30 days of purchase — doing survey after 1–3 days of purchase, recommending complementary product after 4–15 days of purchase, moving into retain customer group after 30 days of purchase.
  3. As an EC platform sales operation, you want to push rewards, vouchers, or promotion codes to customer cluster qualifying label conditions.
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360 view of data for marketing

Recommendations to Shorten Purchase Path

This solution is applicable to the following scenarios:

  1. As a data analytics team staff, you want to quickly try out and evaluate the effectiveness of a brilliant idea you thought by combining labels into your personalized recommendation system.
  2. As a telesales, you want to have a script and a recommended product list to when calling your customer list.

Concept Architecture

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Consumer Insights architecture diagram

Consumer Insights comprises a set of powerful platform services and following highlights its unique and key components:

Data Fusion to OneID

Data Fusion and Member Data Modeling ingest consumer-centric data including member data, transaction data, user behavioral data — from online apps or offline systems across organizations and departments — and outputs member mart based on the member data domain model.

One ID mapping. One ID fully leverages the globally linked data instead of fragmented data. It recognizes same-person IDs by graph algorithms, and then connects and prunes IDs to output unified ID clusters representing natural persons. For example, an e-commerce company may have individual accounts in EC mall app, offline customer databases, OneID will see an integral unified ID without seeing siloed IDs so that we will be able to engage the company accordingly.

Label Factory and Algorithmic Labels

Label Factory provides a user interface to define and generate labels, which can be referenced from the common label library and, more, fully user-customizable labels. It processes and analyses the unified consumer data to produce the profiling attributes.

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Examples of attributes

The profiled attributes are of types as natural, behavior, consumption, and preference. It has to be noted that, beyond traditional statistical attributes, it has ability to simulate “insightful” attribution by using big data algorithms; for example, those of value stratification, churn prediction, conversion prediction, and target population recommendation.

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Predictive Attributes

These generated attributes are not static; they will be automatically processed and updated in a periodic basis, as defined by you, based on the attribute’s trait.

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Label Library

Crowd Insights

Crowd Insights provides ability to screen consumers with ad-hoc queries on tags to form a crowd. You can look into the portrait of the crowd, and then can, for example, push a campaign and utilize the funnel chart to evaluate the effectiveness.

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Consumer Portrait and Effect Evaluation

Implementation Flow

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The steps to adopt Consumer Insights are described as follows:

First, performs member data modeling and OneID mapping to create unified member data of your own. Second, designs and generates labels, and then the admin will manage crowds. Third, the data can be served — via APIs or export functions — to applications like a Customer-360 application, or the Marketing tool, to make them “insightful”.

How to Start?

Interested? Contact our Global Sales Team for assistance. We have industry experts to provide you with professional advice and to work together with you to build the insights of consumers. After all, Consumer Insights is a solution from Alibaba Cloud Data Intelligence, extending Alibaba’s retailing- and member-centric core capabilities to you.

Reference:https://www.alibabacloud.com/blog/consumer-insights-empowering-customer-360-and-precision-marketing-with-data-intelligence_594493?spm=a2c65.12601930.0.0

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