the 'truthiness' of marketing attribution

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The Truthiness of Marketing Attribution

Benefits, Drawbacks, and the Criticality of a Strong Data Foundation


Today’s Speaker

Matt Jacobs VP, Strategic Marketing

Origami Logic


73% of CEOs think their CMOs lack business credibility and aren’t the business growth generators they

should be

80% of CEOs claim they’ve lost trust in their marketers

Source: http://chiefexecutive.net/are-cmos-unfit-for-the-job-how-the-ceo-can-make-a-difference/


•  More channels

•  More tools

•  More data

•  ROI demands


Attribution is so hot right now


Brands are trying to answer two critical questions

Marketers are securing budgets for Attribution and Marketing Mix Modeling (MMM) in hopes of answering the following:

1.  Which channels are driving sales?

2.  How should budget be allocated across channels to maximize sales?


According to an IDG survey, many execs worry about challenges holding back their attribution efforts

More resources are going into analytics tools Attribution is a BIG focus, but the prerequisites are often a bigger problem

mentioned data collection and

accuracy

point to reporting, accountability and

accuracy

said staff skills were problematic

% 50 % 59 % 56

Sources: emarketer, IDG “Executives Reveal Potential Pain Points of Marketing Attribution” – Oct 2015


What’s challenging about attribution?


What are brands trying to accomplish with attribution? The answer can be framed in two ways

1.  What are attribution products designed to do today?

2.  What are marketers trying to use attribution products for beyond what they’re designed to do?

Assign an influence value or “credit” to marketing channels or touch points

•  Obtain a unified view of the customer purchase path across as many channels as possible

•  Analyze cross-channel behaviors to understand the customer journey (“speed to insight”)

•  Leverage the data to fuel interaction strategies – e.g., RTB, personalization, etc.

(“instantly correct course”)


What are brands trying to accomplish with attribution? The answer can be framed in two ways

1.  What are attribution products designed to do today?

2.  What are marketers trying to use attribution products for beyond what they’re designed to do?

Assign an influence value or “credit” to marketing channels or touch points

•  Obtain a unified view of the customer purchase path across as many channels as possible

•  Analyze cross-channel behaviors to understand the customer journey (“speed to insight”)

•  Leverage the data to fuel interaction strategies – e.g., RTB, personalization, etc.

(“instantly correct course”)

Why is this problematic?


Attribution doesn’t address the problem (but claims to!)

Recall the two critical questions marketers are securing budgets to address - and intend to use Attribution to answer:

1. Which channels are driving sales?

2. How should budget be allocated across channels to maximize sales?

Here’s the rub: attribution cannot answer these questions!

Let’s illustrate why…


Most attribution vendors fail to capture reality Apportioning credit to the parts before understanding the whole will often result in the wrong answer

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Most Attribution Vendors Reality

Brand Sales (direct + channel) TV Print Radio WOM PPC Email Display Social Sponsorships

Conversions are influenced by many other channels

PPC

Email

Display

Social

Digital Sponsorships


What ALL attribution vendors get wrong Just because a channel was measurably involved doesn’t mean that channel deserves credit!

PSA

Display Conversions (Attribution)

What’s typically credited

Display Conversions

(Reality)

Naturally occurring conversions that should NOT be credited

Incremental conversions that should be credited

Display Example (illustrative)

Giving 100% credit is deeply flawed


Now you know why most of this doesn’t matter

0% 0% 0% 100% $$

25% 25% 25% 25% $$

35% 15% 15% 35% $$

50% 25% 15% 10% $$

20% 45% 30% 5% $$

40% 10% 35% 15% $$

Last touch

Even weighting

U-based (first , last, middle)

Path position

Attribution pattern

Custom attribution

TBD TBD TBD TBD TBD Algorithmic attribution


Now you know why most of this doesn’t matter

0% 0% 0% 100% $$

25% 25% 25% 25% $$

35% 15% 15% 35% $$

50% 25% 15% 10% $$

20% 45% 30% 5% $$

40% 10% 35% 15% $$

Last touch

Even weighting

U-based (first , last, middle)

Path position

Attribution pattern

Custom attribution

TBD TBD TBD TBD TBD Algorithmic attribution

If you can’t assess lift because the methods you’re using are inherently

wrong, apportioning credit is pointless (and worse than useless)


There’s another skeleton in the closet... Attribution is typically focused on short-term effects and time horizons that are too small to matter

Attribution is often conducted monthly or quarterly, and predominantly relies on cookie data, thus

1.  Limiting the richness of the data set

2.  Skewing results to short-term effects

Makes it difficult to accurately attribute the importance of online touchpoints Biases marketers to allocate budget towards short-term initiatives

Those short-term effects typically comprise 10% - 20% of total sales. The brand – a longer-term asset – accounts for the rest Let’s illustrate why that’s problematic…


There’s another skeleton in the closet... (continued)

When the output of attribution is biased towards short-term effects, the marketing team will maniacally focus on maximizing those drivers (with attribution, that typically means digital channels)

If they work really, really hard, their results might increase sales by 10% (among 20% of buyers)

This situation – which is not an uncommon outcome after attribution – could be remedied with models that account for short and long-term effects, but attribution is not natively set up to accomplish that Attribution can be valuable for surgical micro-changes in select channels, but is not conducive to large budget or channel mix changes (unless you want to lose your job!)

% of Sales % Increase from Op2miza2on

% Increase in Sales

Short-‐term effects 20% 10% 2.0%

Long-‐term effects 80% -‐5% -‐4.0%

Losing focus on the other 80% can generate a net

loss for the business!


Maturity Path: Prerequisites to Attribution


Everything begins with a strong data foundation Multiple steps must be taken to understand MROI and gain the agility to leverage outputs from attribution

When to use over time

Low

M

atur

ity R

equi

red

Hig

h

GET A HOLISTIC, “ALWAYS ON” VIEW OF PERFORMANCE •  Automate multi-channel measurement (collect, cleanse, categorize, structure, enhance, harmonize) •  Harness multi-channel and audience data to develop reporting and establish org-wide knowledge •  Conduct exploratory analyses, create hypotheses for testing

ASSESS AND DETERMINE LIFT •  Conduct channel and audience tests to quantify naturally occurring conversion volumes •  Test investment allocations and understand outputs before attempting Attribution or MMM •  Observe effects across channels to develop new testing hypotheses

ESTABLISH YOUR DATA FOUNDATION AND MEASUREMENT FRAMEWORK •  Complete a measurement plan and data flow schematic for all key touch points in the customer journey •  Implement measurement to assess individual channel performance •  Expand measurement to additional channels, leveraging tag management and data distribution utilities as needed

3 2

1


Marketing measurement and optimization is required thereafter…

Signals from all channels are brought into a solution and organized into a marketing context. Validation, gap filling, back-fetching, and other activities are conducted to further refine the data

Data is then enriched and harmonized. Tagging, comparisons, adaptive aggregations, calculations, and segmentation are completed

Results are expressed via story feeds, dashboards and other visualizations. Search, filtration, collaboration, altering and notifications


Where different approaches complement one another

Comprehensive Marketing Performance Management

Data Collection and Refinement (collect, cleanse, categorize, customize, and harmonize all marketing data)

Analysis and Exploration (channels, campaigns, creatives, audiences)

Data Activation (alerting, reporting, dashboards, visualization)

Factors in all channels?

Uses algorithms/rules to assign “credit” to channels?

Can simulate outcomes at different investment levels?

Calculates interaction effects between channels?

Designed for frequent use throughout Marketing?

Creates a unified view of customer interactions (user level)

Informs personalization and customer engagement efforts

Capable of acting on interaction strategies (testing, RTB, etc.)

Marke2ng Mix Modeling

Marke2ng Measurement & Op2miza2on

AIribu2on


How sophisticated does your organization need to be?

Low Required Analytical Maturity of Marketing Org. High

Low

C

ost,

Effor

t, a

nd T

ime*

Req

uire

d H

igh

* Time = time to implement and time to results

Marketing Measurement &

Optimization

Attribution

MMM


How actionable and frequent are the outputs?

Low How actionable are results / efforts? . High

Low

F

requ

ency

of U

se `

H

igh

Marketing Measurement & Optimization

Attribution

MMM


What’s the sweat-to-equity for each approach?

Low How actionable are results / efforts? . High

Low

C

ost,

Effor

t, a

nd T

ime*

Req

uire

d H

igh

Marketing Measurement &

Optimization

Attribution

MMM

* Time = time to implement and time to results


Where is this all heading?

1.   Marketing signal measurement will continue to evolve as the core data and reporting foundation for marketers •  Enhanced data collection, customization, harmonization, exploration and visualization •  Reconciliation for attribution and MMM

•  Data exhaust as fuel for mix modeling

2.   Attribution and MMM advancements will address historical shortcomings •  Better integration for offline and mobile data •  Reduced focus on “crediting,” and more on providing a unified view of the customer journey

•  Convergence of multiple capabilities (e.g., attribution, MMM, testing, ad tech, etc.) •  Blended analytical approaches will become the new norm


About Origami Logic

Helping Global Brands Master Their Marketing Performance

Tier-1 Investors

Experienced Leaders & Domain Expertise

Rapid Deployment with Smart Services

Agility with Daily Insights

Search and Organize with

Dynamic Data Model

Unify All Campaign Performance Data

Our Platform


Thank You

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