Lecture 2 Flashcards
(43 cards)
Shoppers once relied on a familiar salesperson to find what they wanted. Today…
Today’s distracted consumers, bombarded with information and options, often struggle to find products
Salespeople would draw on their knowledge or quickly deduce about customer, locate the perfect product and suggest additional items. Today…
- Shorthanded retailer floor staff can’t replicate the personal touch that shoppers once depended on
- Consumers are still largely on their own when they shop online
IDC predicts that the “digital universe” (the data created and copied every year) will reach __ ___ (180 followed by 21 zeros) in 2025
180 zettabytes
Poor __ __ is enemy #1 to the profitable use of
machine learning
data quality
To properly train a predictive model, historical data must meet these exceptionally broad and high quality standards
- Data must be right (i.e. correct, properly labeled, de-duped)
- But you must also have the right data (i.e. unbiased over the entire range of inputs leveraged to develop the predictive model)
In a study involving 75 executives, only __ found that their departments fell within the minimum acceptable range of 97 or more correct data records out of 100
3%
How to Improve Data Quality
- Clarify your objectives and assess whether you have
the right data to support these objectives - Build plenty of time to execute data quality
fundamentals into your overall project plan - Maintain an audit trail as you prepare the training data
- Charge a specific individual (or team) with responsibility for data quality
- Obtain independent, rigorous quality assurance
Customer Data
1
Name, Date of Birth, Gender, Postal Address, Telephone, Email, Social Network
Profiles, Account Info, Job Info, Income
2
Transaction (offline & online), Communication, Online Activity, Social
Network Activity, Customer Service
3
Attitudinal Info, Opinion, Motivational, Interests
4
Family Details, Lifestyle Details, Career Info
How to Collect Identity Data
POS System & Online Transaction Database
Clienteling
Social Network Profile & Other Customer Profile Features
3rd party data sources
How to Collect Quantitative Data
Transaction Database
Web Analytics Tool
3rd Party Pixels
In Store Tracking
Google Analytics & Adobe Analytics are platforms that
collect online data and compile it into useful reports
To start collecting data you need to create an account and add __ __ to your site
javascript code.
Every time a user visits a page, the code will collect interaction data and other information from the browser (i.e. language, type of browser, device, etc…)
Web Analytics tools allow us to track every action the
customer is performing on a website:
Browsing Behavior
Search Data
Purchase History
The Challenge of Web Data
Unique visitors does not necessarily mean unique customers
One customer may be tied to multiple cookies (see slide 29 on how to solve it)
T/F
Online retailers know so much more about their customers than their offline counterparts
True
__ __ have created direct connection to their customers, which in turn allows them to collect massive amounts of data about them
Online retailers
Through AI, online retailers are able to create more-personalized…
…customer experiences, fostering levels of satisfaction, connection, and customer loyalty
Amazon has created a new digital marketing model based on a
1-to-1 relationship with the customer, informed by data collection, optimized with machine learning, and nurtured with other forms of AI
3rd Party Pixel Tracking is a tool used to
track and analyze website traffic, individual user behavior, and ad impressions
Hidden in the background of a web page or email so that they aren’t part of the user’s experience
They are complementary to your web analytics tool
New technology can track live foot traffic in a store and
break down shoppers into a variety of data segments
In Store Tracking–Data is pulled from
IoT sensors, beacons and branded app
In Store Tracking
Additionally, depending on the retailer, data is also taken and
joined to POS systems and online data
On an average, consumers in the US use
4 devices each day
predicted to increase with IoT
companies use multiple tools to store different customer attributes (i.e. CRM, Email, Ecommerce, POS, Social Media)
CRM, Email, Ecommerce, POS, Social Media)
