sitecore: understanding your visitors and user personas

Amsterdam Las Vegas Melbourne

Delivering on the Potential

of Personalization

Randy Woods | Amanda Shiga

non~linear creations

What We’ll Say

• Personalization capabilities in context

• Knowing your visitor

• Building your rules

• Real world implementation considerations

• Questions and answers

Amanda Shiga Director, Websites and

Digital Marketing

Sitecore MVP

@amandashiga

ashiga@nonlinearcreations

+16477762658

Randy Woods President of NLC

@randywoods

rwoods@nonlinecreations.

+16136910978

And You?

PERSONALIZATION IS EVIL

Section one

Much of the Web’s future will come from delivering individualized experiences

Josh Bernhoff, Forrester Analyst

May, 1996

At its best, personalization is motivated by a desire to make human connections on a

non-human scale

Randy Woods

Just now

KPIs should be viewed as

positive byproducts of this

intent • Increased conversion rate

• Increased subscriptions

• Improved click-throughs

• Higher average revenue per basket

• Shortened sales cycle

Why Should We Care?

Here’s Why: A Cautionary

In 3 days DoubleClick's stock experienced a 20-

point loss

Six lawsuits; state investigations

A $1.2 billion loss

But that can’t happen now,

right?

But We’re Not Facebook

You need to derive personalization rules in the same way that we interact in the real

world – from insight into the needs of your visitor

KNOWING YOUR CUSTOMERS

You are NOT your visitor

You are not your visitors

• Personas:

– Archetypes who

represent a group

• Useful for building

personalization

rules but have

specific limitations

Personas and Types of

Personalization Implicit Personalization

• The visitor has not self-

identified

• Rules are based on what

you can observe about

the visitor

– “Digital finger print”

– “Digital body language”

Explicit Personalization

• Visitor has made contact

and provided information

• Rules are based on what

visitor has told you:

– Title

– Gender

– Previous purchases

Buying Cycle

For implicit personalization, personas matter only in so far as they can be

discriminated from each other based on the content the visitor views

Developing and Validating

Personas

1 Identify Ad Hoc Personas

2 Collect User Data

3 Analysis

4 Review and Prioritization

5 Flesh our Personas

6 Communicate to Organization

2 Collect User Data

5 Flesh our Personas

Conceived Personas

Analytic Data

BUILDING AND EVALUATING

YOUR RULES

72 Dimensions

The “Buying” Cycle –

Personas in Time

Basic Information Gathering

Detailed Information Gathering

Narrowing Scope

Validating Understanding

Selecting a Contender

Negotiating Close

Map the Buying Cycle

Narrowing Scope

Negotiating Close

How do these software- as- a- service (Saas) products

compare to the on- premises solutions?

Our HR management system is down again. There must be

something better out there.

Can these three SaaS HR solutions meet our needs?

What do they cost? How stable are they?

What do the analysts think

of HRX-online? What

do current users think?

The pricing the sales person gave me seems okay. And the special only runs until end of

quarter

Now I just need to get finance involved. Oh, and IT to

decommission the old system.

Wow. That took longer than expected. I’m glad we’re finally

The “Buying” Cycle:

The Implicit > Explicit

Transition

Narrowing Scope

Negotiating Close

The Handoff

Personalization Paradox

Geography Search Term

Company

Content Viewed

Clickstream

Accuracy of Persona match

Gender Previous

purchases

Social interactions

Building Personalization

Persona + Buying

Cycle Stage = Interest

Content you

believe will move cycle

forward

Analytics

Evaluating Success of

Personalization Rules

Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Month 7 Month 8

Persona A Control Persona A Rule 1 Persona A Rule 2

Evaluating Success of

Personalization Rules • Key question – does a given personalization rule

increase or decrease business outcomes for a specific persona?

• You need to establish a baseline for each persona

• Custom queries can help you answer this question; the upcoming release of OLAP capabilities will make this simpler

Personalization is not always the answer

Three Times You Don’t Need

Personalization You are generating lots of names for sales – but few qualified leads:

• Engagement Plan and Lead Scoring

Conversion rates are very low and you don’t know why:

• A|B or Multivariate Testing

You don’t understand your visitors or you can’t measure the success of the personalization rules you make:

• Engagement Analytics

REAL WORLD IMPLEMENTATION

CONSIDERATIONS

2 key implementation

considerations

• Start simple, and stay tightly focused on

highest value campaigns

• Be strategic as your users evolve from

strangers to real people

Keep it simple

Strategic planning Rules management Content variations

Measurement mechanisms

Quality assurance Analyze & optimize Impact on build

Content profiling

Strategic planning Rules management Content variations

Content profiling Strategic planning Rules management Content variations

Content profiling

What’s manageable?

• Personalization is complex

– Needs marketing attention, time, energy and

dollars

• You have a good chance at early success

if you:

– Begin simply and target an important

objective

A simple example

• Establish a baseline so you can measure

success

• Select a discrete, important goal and

segment

– Corporate priority is increased membership.

– “We would like more beginner kite-flyers in

Nevada to join our Kite Flyers Association.”

A simple example

• Identify where in the buying cycle

personalization will be most effective

– Inspect profiled content and your buying cycle

– Start with just a few components

– Document your personalization plan

A simple example

• Beginner kite flyers in Nevada:

– Geo-IP lookup

– Browsing behaviour focused on content targeted to beginners.

• “How to fly a kite”

• “Different types of kites”

Best positioned to

influence…

Narrowing Scope

Negotiating Close

A couple of good ideas…

• “Interested in learning more about kite-

flying?” message in the right-hand rail,

promoting membership benefits

• A personalized “Join Now” call to action

displayed in the header, promoting local

Nevada chapters

Analyze and optimize

• Evaluate membership conversions against

baseline

• Use DMS goals to determine success of a

• Eliminate rules that are not effective

• Examine behaviours and clickstream of

visits resulting in conversion

Content architecture matters

Be strategic

• Plan for growth and multiple campaigns

• Understand how components will be re-used across the

• Plan for WHO will create and maintain both the rules and

variations

• Consider where and how the variations will be stored

• Multiple ways to approach this - do not underestimate.

– Talk to your architectural team early, and often.

Be strategic as your users evolve

from strangers to real people

We were all strangers,

once…

Anonymous visitor

Building a profile

Conversion to known user

One view of the customer

• Implicit: beginner kite flyer from Nevada

who searched for “kite flying lessons”

• Explicit: association member

member Name Age

Groups

Interests

The opportunity

• Leverage known user characteristics (by extending the user profile) and…

• Actions that continue to be taken on the site – increase of engagement value or specific conversions

– pattern matching to multiple personas

Where user profile “skill level” field is equal to “intermediate”

And where the Engagement Value Points is greater than 200

And where the current visit matches the “Mike” pattern card in the “Personas” profile

The challenge

• One user profile

• (Potentially) multiple browsing sessions

• Achieving “one view of the customer” can

be difficult

The challenge

Some suggestions

• Do your visitors spend significant time logged in?

– Place a value on browsing behavior that occurs anonymously vs. not

• Consider limiting your personalization rules to what is known within one session

• Consider updating the user profile explicitly with behavioural characteristics as they become known

Don’t be creepy

Don’t be “that guy”

• Play it cool

• Don’t move too fast

• Nobody likes a stalker

• A two-way conversation

Be careful of assumptions

• ~40 Sitecore deployments

• 150+ CMS deployments

• 2 Sitecore MVPs

• Multiple Sitecore site of the year winners

• 80+ team members in offices across the US, Canada and Brazil

• Our strategic services team has been helping clients execute DMS-type campaigns since 1999

QUESTIONS AND (IDEALLY)

ANSWERS

Feedback Appreciated!

Please take a moment to provide session feedback via the mobile site.

http://www.sitecore.net/SymNA

sitecore: understanding your visitors and user personas

contenderlas vegasmelbourne

nowamsterdamlas vegasmelbourne

building personalization

information rules

personalization capabilities

buying cycle personas

selfidentified rules

cycle stage

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