Paid Social Advertising: Now, Next and What Works Best

SEATTLE INTERACTIVE CONFERENCE

Paid Social Advertising: Now, Next and What Works Best

Why are we talking about search in a discussion about paid social?

The early days of search

• Marketers’ dream comes true

• We built it, they came

• Few tools, big results

• Highly targeted, reactive – Customers flocked to us

• At low cost

Search was brilliant.


The middle years

• Battle for top rankings intensifies

• Fierce competition for keywords

• The age of SEO begins

• Fuzzy metrics

• ROI uncertain

• Enter paid search


Today

• SEOs have tried all sorts of things

• Diminished search experience

• Algorithms (Vince, Panda)

Most brands have to pay for reach and scale

• Brands can’t control search results

• Paid Search is a multi-billion dollar a year industry.

Current Landscape

Social Marketing Today

• Social reach in decline

• Battle for the newsfeed

• Algorithms control eyeballs

Brands have lost control of who

sees their social content. Sound Familiar?

• Confusing metrics

• If brands build content, consumption is not guaranteed. This is a problem.

• Enter Paid Social

Current Landscape

Search Marketing Today/ Social

Climate Visibility in decline Reach in decline

Battle Zone Newsfeed Front Page

Control Algorithms Algorithms

Targeting Gender, age, geo Keywords

Metrics Confusing Fuzzy

Current Landscape

Social Marketing Today

• Followers, retweets

• Fans, likes, comments, shares

• Likes, comments, shares

This model leaves lots of unanswered questions

Current Landscape

Who is on my social channels?

Why is it important to know?

How you can find out?

What to do with the information?

Current Landscape

How can I reach them?

• Location

• Age, Gender

• Interests

• Behavior

• Education Levels

• Connections

• Keywords

• Interests

• Location

• Gender

• Language

• Devices

• By job title and function

• By industry and company size

• By seniority

FACEBOOK TWITTER LINKEDIN

Current Landscape

What content is working?




Current Landscape

Who is sharing it?




Current Landscape

Limitations

The customer journey is not limited to just social channels

Analytics should give deep insight across channels

Multichannel/Full Lifecycle approach to managing the customer experience

The future of social advertising

Programmatic

• What does programmatic mean to you?

• Then & Now


Audience Profiles

• The best audience profile is data-driven

• Utilize a combination of native targeting on social networks in addition to your first-party data

• First-party data

• Social network native targeting


Audience Profiles continued…

3 KEY WAYS OF TARGETING AUDIENCES ON FACEBOOK AND TWITTER:

1. Core Audiences

2. Custom or Tailored Audiences

3. Look-a-like Audiences


Social Retargeting

Why retarget?

How do you retarget?

What are the use causes?


Forecasted campaigns and predictive analytics

• A single source of truth bringing data together

• Adopt consistent ad tech and marketing tech solution

• No single user journey is the same

• Leverage other unique data points such as rich analytics data as early signals that correlate to a conversion rate to address data sparsity issues.


Predictive analytics to inform ad buying

Some company have access to hundreds of analytics metrics

Identify ones that have a high correlation with conversion rate and leverage as revenue signals. This may differ from industry vertical to vertical.

Common revenue signals are:

1. Page views in the first visit

2. Total time spent on multiple visits

3. Bounce rate

4. Total page views across multiple visits

5. Time spent onsite in first visit


Best practices for targeting in a multi-channel ecosystem

• Common business objectives

• Leverage customer profiles & audience targeting

• Segment audiences at scale and test different levers that influence performance

• Leverage early predictors of performance using web analytics

• Optimize channels holistically to maximize digital ROI

• Experiment and iterate

Case Studies

Lead Generation for Education client

OBJECTIVE: TEST AND MAXIMIZE FULL POTENTIAL OF 1ST PARTY CRM DATA

Solution: Test overlay of core native targeting with Look-a-like targeting

Results: Benchmarked against Core native targeting on Facebook

Click through rate increased +447%

Conversion rate increased +51%

Cost per lead improved 46%

Solution: Look-a-like audiences generated from Custom Audiences

Results: Benchmarked against Core native targeting on Facebook

Conversion rate increased +199%

Cost per lead improved by 59%

-66%

-45%

-5%

3%

4%

166%

100%

-4%

1%

-14%

-100% -50% 0% 50% 100% 150% 200%

ROAS CPO

Case Studies

Online sales for eCommerce client

LOOKALIKE AUDIENCES

LIKES & INTERESTS

LOOKALIKE AUDIENCES

+ LIKES & INTERESTS

CUSTOM AUDIENCES

WEBSITE CUSTOM AUDIENCES

Custom audiences & other Audience Targets relative to avg. CPO and ROAS

0%

2%

4%

6%

Search Behavior Lifetime Website Custom Audiences Last 60

Days

Search Behavior Last 7 Days

CTR CVR

Case Studies

Online sales for Travel client

ROAS: 5.69 6.64 8.11

OBJECTIVE: DRIVE INCREMENTAL SCALE BEYOND SEARCH, COST-EFFICIENTLY

Solution: Social retargeting through Website and CRM Custom Audiences

Results:

Case Studies

Online sales for Travel client

0.41% 0.61% 0.50% 0.56%

1.02%

3.06%

8.25%

9.70%

0%

2%

4%

6%

8%

10%

12%

Engaged Newsletter

Subscribers

High Value Customers Lower Tier Loyalty Program Higher Tier Loyalty Program

CTR CVR

ROAS: 5.69 12.12 15.55 24.85

Thank You

Paid Social Advertising: Now, Next and What Works Best

Marketing

Transcript of Paid Social Advertising: Now, Next and What Works Best