Performance marketers are consistently investing in new opportunities and techniques to drive cost efficiencies with their advertising strategies, but are they effectively utilizing the data they already have? Online and offline behaviors are the some of the best signals for understanding consumer intent, but when treated equally, can create just as much noise as they do value. Vivian Nantembe and Stu Richards from the Catalyst team will be exploring:
- How brands can surface data about their site visitors’ user journeys
- Best practices for analyzing the user journey to understand what pages drive success/key actions
- A methodological approach to create a weighted optimization strategy
3. Instructions
3
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4. 4
Business Results.
Powered by Advanced Marketing Strategy.
Organic Search | Paid Search | Paid Social
Programmatic | Retail Media
7. THERE IS NO FORUMLA
7
Introduce the concept of weighted metrics and
optimizations
Explore how they can be uniquely developed for different
advertisers
Understand how they can be implemented across channels
Examine the efficiencies they drive when incorporated into
a media buying strategy
8. Media Value Assessment
8
ASSESSMENT
MODEL
WHAT IS IT? CALCULATION PROS CONS RATING
CPC Cost Per Click Media Spend / Clicks Lots of data Poor quality performance signal 2
CPLP
Cost Per Landing
Page
Media Spend / Landing Page Visits Good signal of media interaction Doesn't account for post-land actions 3
CPPV Cost Per Page View Media Spend / Page Views Accounts for all site interaction Doesn't discern the value of the action 4
CPA Cost Per Action Media Spend / Actions Strong signal of intent Doesn't account for value of intent 6
ROAS Return on Ad Spend Purchase Revenue / Media Spend
Accounts for value attributed to
action
Only accounts for a moment in time 7
LTV Lifetime Value
Sum of All Purchaser's Revenue / Media
Spend
Accounts for the value of a
consumer
Data scarcity 8
LTV + Influence
Lifetime Value +
Influence
Sum of All Purchaser's Revenue +
Influenced Purchase Revenue / Media
Spend
Very difficult to account for Data scarcity and attribution of influence 9
• Ratings are solely my opinion and do not reflect Catalyst's stance
• Not all advertisers are created equal – although possible, ROAS + LTV very difficult for advertisers who distribute through brick and mortar
MEDIA
TRAFFIC
REVENUE
9. • Multinational refrigeration brand
• Distributes to multiple brick-and-
mortar resellers
• >$100M annual revenue
Our Examples
9
CAN PURCHASE ONLINE
LOW LEVEL SALES
OPTIMIZING TO CPO
CAN'T PURCHASE ONLINE
HIGH LEVEL SALES
OPTIMIZING TO CPRL
KAYLEE'S
FROST
• Luxury DTC leather goods startup
• Sells exclusively on their
eCommerce site
• <$1M annual revenue
11. User Journey
11
USER & SOURCE PAGES VISITED PURCHASE & REVENUE
$399
$2,299
About
Us
Sustainable
Fashion Blog
How We Give
Back
About
Us
Sustainable
Fashion Blog
$7,299
12. ???
???
$7999
User Journey
USER & SOURCE PAGES VISITED PURCHASE & REVENUE
DIRECT Product Registration Page
Where to Buy
Where to
Buy
About
Us
13. 13
• Site analytics tools are great, raw data is most powerful due to path
• Segment based on valuable actions, values associated to valuable actions
• If data for valuable actions is scarce, take a step back
AGGREGATED SITE ANALYTICS LOG-LEVEL USER DATA
Assessment Tools
15. 15
• Analyze the difference between those taking valuable actions and the average site visitors
• Ratings are solely my opinion and do not reflect Catalyst's stance
• Not all advertisers are created equal – although possible, ROAS + LTV very difficult for advertisers who
distribute through brick and mortar
ANNUAL
REVENUE:
$800K
MONTHLY
VISITORS:
24K
AVERAGE
PURCHASE:
$277
DAILY AVG
PURCHASERS:
8
ANNUAL
REVENUE:
$126M
MONTHLY
VISITORS:
350K
AVERAGE
PURCHASE:
???
DAILY AVG
PURCHASERS:
???
Assessment Analysis
16. 16
• Analyze the difference between those taking valuable actions and the average site visitors
• Ratings are solely my opinion and do not reflect Catalyst's stance
• Not all advertisers are created equal – although possible, ROAS + LTV very difficult for advertisers who distribute through
brick and mortar
Index = (Checkout-ers/Avg Visitor) * 100
Assessment Analysis
17. 17
• Fragmented sales data is confusing and time consuming to analyze
• Need to find a digital action point that correlates with sales
REVENUE
FINDARETAILERVISITS
LOCATIONS
jane.harris@email.com
jane.harris@email.com
Assessment Analysis
26. KNOW YOUR DATA:
Audit & understand all available data for
analysis.
DON’T COMPARE APPLES TO ORANGES:
Don't compare what you have been doing to
what you're now doing.
APPLY TO ALL CHANNELS:
Once you've developed your weighted
optimization strategy, don't implement it in
siloes.
26
Recommendations
IMPROVE AND REFINE FREQUENTLY:
Re-assess and analyze your data frequently
to keep in line with current consumer
behavior patterns.
DEVELOP FIRST TO MARKET
OPPORTUNITIES:
This process involves work, but with your
insight, you can develop your own bespoke
initiatives.
BRING IN OUTSIDE DATA:
Brainstorm what other data could help
improve your optimizations.
27. Key Steps for Custom Optimizations
27
1. Collect all available data at your disposal
2. Analyze the value of each digital interaction
3. Create a set of weighted scores based on these digital interactions
4. Build the weighted scores into your omnichannel reporting
5. Optimize media budgets based on weighted scores
6. Repeat steps 1-5
1.
2.
3.
4.
5.
6.
29. Digital commerce thought-leadership to
help advertisers maximize success in
the new world of commerce.
Topics include shopper insights,
Instacart Advertising, omni-channel
strategy & execution, retailer
partnership, & more.
Additional Resources: Virtual Event Series
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Every Wednesday, 1 – 2:30 pm ET
www.catalystdigital.com/the-new-commerce-conference