The document discusses how marketers can use different types of consumer data for predictive analytics. It explains that websites visited can help predict purchase likelihood. Level of engagement data like pages viewed and return visits can also be used. Consumer interests, lifestyles and personalities revealed on social media can provide insights. Purchase history details such as abandoned carts and returns allow analysis of consumer behaviors. Predictive models help businesses attract, retain and profit from optimal customers.

1. PRESENTATION ON
GROUP MEMBERS
ADIL
AFZAL
MUKESH
AFTAB

2. Q.10 Explain how marketers can use each of the following
pieces of data in predictive analytics:
A. The website consumers visit.
B. Consumers’ level of engagement with visited website (i.e. ,
the page viewed, length of visits, frequency of the return to the
site).
C. Visitors’ and consumers’ interests, lifestyle, and
personalities(e.g. from the contents of their blogs, tweets, and
face book profile).
D. Visitors’ purchases, almost purchases, abandoned carts, and
product returns and exchange.

3. PREDICTIVE ANALYTICS
 Predictive analytics are used to determine
customer responses or purchases as well as
promote cross-sell opportunities.
 Predictive models help business attract, retain
and grow their most profitable customer,
improving operation.

4. THE WEBSITE CONSUMER VISIT:
 Propensity models, also called likelihood
to buy or response models, are what most
people think about with predictive
analytics. These models help predict the
likelihood of a certain type of customer
behavior, like whether a customer that is
browsing your website is likely to buy
something. This helps marketers optimize
anything from email send frequency, to
sales staff time, to money, including
discounts.

5. • Getting deep into your data is a great way to determine the most cost-
effective customers across the entire lifespan, and to help determine
the best customer acquisition marketing efforts. However, predictive
analytics can also be applied to two other marketing pain points:
keeping existing customers, and retargeting those customers who are
no longer actively buying from you.
• Sure Google, Yahoo, Cnn, Craigslist, Amazon, Ebay, New York
Times are always going to be there. It might even seem like things
never change.
• Unfortunately for you and I the game is not quite the same. The web is
constantly changing. The way people experience it, the way people
compete, the way people read and recommend and buy, the way
everything happens.

6.  No of times consumer visit to web site.
 Viewing brand focus page.
 As face book page.
 How long customer stay on web site.
 Locating your new vs returning visitor metrics.
 No of times consumer return to site.
B. Consumers’ level of engagement with visited website
(i.e. , the page viewed, length of visits, frequency of the
return to the site).

7. C. Visitors’ and consumers’ interests, lifestyle,
and personalities (e.g. from the contents of their
blogs, tweets, and face book profile).
 A set of shared values or tastes exhibited
by a group of consumers especially as
these are reflected in consumption
patterns.
 Lifestyle means the ways groups of
consumers spend time and money.
Lifestyle can include things like bowling,
cooking, car racing, kayaking, attending
charity events, having pets, interest in
politics, watching sporting events and so

8. Personality traits
 Openness.
 Conscientiousness.
 Extraversion.
 Agreeableness.
 Neuroticism.
From the face book profile , twitter
marketer can get information related to
the behaviour of the consumer.

9. D. Visitors’ purchases, almost purchases,
abandoned carts, and product returns and
exchange.
 Convert visit into purchase.
 On line booking.
 Apps.
 Website of the company.
Abandoned cart emails are sent to
customers who have added products to
their cart but failed to check out.

10. • Online deal.
• It’s like finding cash in your coat. You’re forgetful sometimes,
and so are your customers. Our abandoned cart messaging can
help.
• Return policy.
ex: return by email
• Return in store
• Exchange policy .