digital marketing roi - an introduction to attribution modelling

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Digital Marketing ROI: An introduction to attribution modelling

@bloomworldwide

www.bloomworldwide.com

[email protected]


Introduction 5

Chapter 1: What is attribution modelling? 6

Why bother? 7

Return on investment – Not ROI 7

What is it? 7

The different models 8

Chapter 2: Before we begin 9

In a hurry? 10

Illustrating the different models 10

‘Finding Your Attribution Solution’ – visual guide 11

What we will cover 12

What is a conversion? 12

Chapter 3: Last Click – everyone’s first model 13

What is it? 14

Pros 14

Cons 14

When to use it 15

Chapter 4: First Click – Last Click’s mirror image 16

What is it? 17

Pros 17

Cons 17

When to use it 18

Chapter 5: Last Non-Direct Click and similar models 19

Notes on this chapter 20

What is it? 20

Pros 21

Cons 21

When to use it 22

Chapter 6: Linear – equal credit to each touchpoint 23

What is it? 24

Pros 24

Cons 24

When to use it 25

Content


Chapter 7: Positional – location, location, location 26

What is it? 27

Pros 27

Cons 27

When to use it 28

Chapter 8: Time Decay – not as ominous as it sounds 29

What is it? 30

Pros 30

Cons 30

When to use it 31

Chapter 9: Customisation – the better model 32

Time 33

Channel 33

Position 33

Weighting 33

Any combination of the above... and many more 34

Chapter 10: A very social media 35

Demonstrating the value of social media 36

Social media and attribution modelling 36

Conclusion 37

Pictures 37

Where next? 37

Get in touch 38


In the late 1800’s, Sir Arthur Conan Doyle penned the above line for the world’s pre-eminent detective. 125 years later the majority of people still don’t adhere to its message.

It is a capital mistake to theorise before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.

Sherlock Holmes ‘A Scandal in Bohemia’

5

Introduction

Attribution modelling is the method used to measure the

monetary impact a piece of communication has on real

business goals, for example: sales, customer retention,

revenue and profit.

It is a ‘catch-all’ term for changes to reporting structure and communication

that allow us to move away from the familiar reporting language of digital

marketing (time on site, engagement rate, click through rate, etc.), and translate

these metrics into the valuable language of business reporting (volume of

sales, net profit, percentage of returning customers).

And critically how to do this efficiently, accurately and exhaustively.

This paper will explore what attribution modelling is, how to implement

it, and review common attribution models, which will help define the best

starting point for your business.


Chapter 1: What is attribution

modelling?


Return on investment – Not ROIThis is what attribution modelling does; it attributes a monetary value to every piece of communication, allowing you to

accurately measure the value of your efforts in terms of return on investment, the amount of money you get versus the amount of

money you spend.

Too often, ROI is discussed in non-financial terms. People forget what ROI means – return-on-investment – and talk about, for

example, the extra conversation you generated, or the improvement you delivered in your search page ranking. These could be

seen as digital ROI, but they are not real, financial ROI. Only this measurement allows you to accurately make informed decisions

on budget allocation and which marketing activities will deliver on business goals.

This is the primary objective of attribution modelling; to provide holistic, accurate information about the financial return activities

are delivering so you can refine them, adjust what you’re doing, and use the same budget to deliver more value to your business

and your customers.

Why bother?There is a good chance that you’re already doing some form of attribution modelling and, when you look at its meaning, you’ll see

why. Attribution modelling means defining a system of analysis that can be used to measure marketing metrics against business

results. This means reporting on the impact of communication activity using metrics like:

• Turnover

• Profit

• Customer retention

• Volume of sales

Instead of metrics like>

• Share of voice

• Web visits

• Click through rate (CTR)

• Impressions

There’s a big difference between these two lists. The second list contains important metrics, but businesses, in theory, could

survive without ever increasing them. However, the business metrics in the first list are essential for all companies that want to

survive and thrive. Without them a business won’t grow, and it won’t last.

Understanding the impact on business metrics is – rightly – more important to senior executives.

What is it?As mentioned, there is a good chance that you’re already undertaking some system of reporting on business metrics, and

therefore are – at least in its purest form – already modelling attribution.

However, the term ‘attribution modelling’ has come to mean the discipline of doing this in a scalable, representative and holistic

way.

If you work for a business that sells online you will have seen - and maybe produced - reports that showed X% of website sales

were driven by PPC, and therefore PPC delivers £X thousand at a cost of £Y thousand.


The different modelsThere are a number of technology vendors who can implement tracking, tags, tag containers and similar services that will

accurately gather the data you need. However, this paper focuses on analysis, and what you can do with the information once

you’ve got it. This is what changes dramatically from business to business.

We will look at common attribution models (or sets of rules) and when they should and shouldn’t be used to attribute results to your

marketing activity.

To get the data, you need –

TechnologyBy implementing the right technology, you can start gathering the

information about where your different digital touchpoints appear

in the customer journeys.

There are several ways to do this and the most common is to

implement tracking tags across all online activity.

Tags allow individual user journeys to be tracked and analysed to

see exactly how users behave when they are exposed to different

marketing activities. This can all be done anonymously so you’re

never violating users’ privacy.

It is worth emphasising that even without the right technology in place, there is a great deal that can be done with the data you

already have. By digging into the data you already have, and looking at how it relates to business performance, you can make great

progress towards developing an attribution model.

However, you know from experience that this is not the full picture. It doesn’t take into account the awareness-generating PR

you conducted, or the affinity you created through your social media activity, or any of the countless touch points a consumer

had with your brand prior to the purchase decision. PPC absolutely had a role to play but it wasn’t responsible for 100% of that

purchase, you just don’t have the data to prove it. The right attribution model will give you this information.

There are 2 steps to putting an attribution model in place>

To understand the data, you need –

AnalysisThe attribution model itself is the set of rules that determine the

value of an interaction or touchpoint in a number of different

scenarios.

By applying these rules to different activities, and comparing the

value that each activity delivers against the amount it costs to

deliver, you can identify the return on investment from each activity;

This approach allows you to ‘deep dive’ into the data – for example,

not only can you determine the value of a tweet in general but you

can determine the exact worth you received from a specific tweet.


Chapter 2: Before we begin


In this example, the customer first encountered the brand through organic search, then through social media, then through an

email and so on. The eighth touchpoint with the brand – a direct visit to the website – was the last and the point at which the

customer made a purchase.

The y-axis details how much of the customer’s spend is attributed to each channel. Here an increasing percentage of spend is

attributed to each channel as the customer moves closer to the point of purchase. This is an example of the ‘Time Decay’ model,

which will be discussed later.

In a hurry?As with everything, there’s always somewhere you can start. No matter what point you’re on in your attribution journey, there is a

small step you can take to move forward.

Bloom Worldwide has created a visual guide to “Finding Your Attribution Solution”, which provides an overview of the most

popular models. This can be seen on the following page.

For those in a hurry, or who want a reminder, it’s worth keeping this infographic to hand.

Download from: http://www.bloomworldwide.com/focus-on/attribution-roi/

Time Decay

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1st: Organic Search

2nd: Social

Media

4th: Display

7th: PPC

5th: Organic Search

6th: Direct

8th: Direct

3rd: Email

Touchpoint

Illustrating the different modelsTo illustrate the different attribution models we will look at a number of examples using graphs like the one below. Each will show

a customer journey from the first touch point to a purchase, and include all the points where the customer encounters the brand.


First Click Positional Last Non-Direct Click Linear Time Decay Last Click

These attribution model recommendations are not based on data and indicative only.

Bloom would like to reiterate that there is no one size fits all attribution solution.

Please get in touch to discuss your business needs further so we can discuss the best model solution for you.

Custom models may be recommended.

YES

NO YES

YES

YES

CONSIDERED

IMPULSE

START

NO

NO

YES NO

NO

What is it? This model gives all the credit to the channel of the first touchpoint your consumer has with your brand.

Why use it? If you’re only advertising in one channel, most of your business can probably be traced back to that channel.

What is it? The position in which the channel appears in your customers’ user journey (first touchpoint, second, third etc.) determines how much revenue they are credited with.

Why use it? Users need time to consider you over multiple interactions, but you can prioritise those that begin and end that process.

What is it? The channel of the last touchpoint your consumer had with your brand that wasn’t a direct website visit gets all the credit.

Why use it? An advertised cheap price or other catalyst could have driven the sale, or made the user decide to return later.

What is it? Every touchpoint that your consumer has with your brand is considered equally, receiving equal “credit”.

Why use it? A long, research-filled user journey with multiple touchpoints working together means each channel should be weighted equally.

What is it? Channels are credited based on the time it takes for the consumer to be exposed to your brand again after the touchpoint.

Why use it? For impulse purchases, less time for a user to find your brand again can demonstrate more impact.

What is it? The channel that drove the user to the visit when they purchased gets all the credit.

Why use it? Your price or offering is likely the revenue driver rather than the channel, so it’s all about how easy it is for a consumer to get to you.

Are you an impulse buy or a considered purchase?

Is your comms activity multi-channel?

Sources: Adobe Marketing Cloud: Quarterly intelligence briefing http://gb.pinterest.com/pin/401805597974345823/ www.selfgrowth.com http://milo.com/blog/the-impulse-shopping-fact-sheet/?display=wide http://baymard.com/lists/cart-abandonment-rate based on 27 different studies http://searchengineland.com/library/stats/stats-spend-projections SlingshotSEO (2012) http://gb.pin-

terest.com/pin/535224736935111683/ Monetate http://gb.pinterest.com/pin/164240717633008003/ Baynote via www.comscore.com http://gb.pinterest.com/pin/46513808623423915/ www.makeusefo.com http://gb.pinterest.com/pin/41869471508424344/ http://www.aldricharchive.com/inventors_story.html Baynote’s fouth-annual E-Commerce Survey developed in conjunction

with the e-Training Group http://gb.pinterest.com/pin/521854675543572316/ www.artisanmanagement.com/abandoned-shopping-carts http://gb.pinterest.com/pin/567664728002056583/ Volusion Marketing Services customer data http://gb.pinterest.com/pin/567523990515758042/

Find out more at www.bloomworldwide.com

The insight driven digital agency specialising in search, social and content.

Follow us on twitter @bloomworldwide

Say hello to us [email protected]

�

‘Finding Your Attribution Solution’ - visual guide


What is a conversion?Throughout this paper we refer to a conversion as a sale,

however, we know that not every online customer journey

ends in a sale. If you are a brand where the purchase happens

either offline, or in a multi or omni-channel environment,

there is still huge value in putting attribution modelling in

place to measure your digital marketing efforts.

The only difference is what you consider as a conversion.

Think about your online customer journey and identify

the points that demonstrably move the customer closer to

purchase. For example, booking a test drive, downloading a

coupon, requesting more information, asking to speak to a

sales representative and so on. Understanding the impact

of different touchpoints on these conversions provides

valuable business information that will help improve your

digital marketing.

What we will coverWhile there are many different ‘off the shelf’ attribution

models, this paper concentrates on six of the most common:

• Last Click

• First Click

• Last Non-Direct Click

• Linear

• Positional

• Time Decay

We also look at how you can customise these models to

create bespoke approaches for different brands. Finally,

we’ll touch on what attribution means for social media, and

provide some useful additional pointers.


Chapter 3: Last Click – everyone’s

first model


What is it?Last Click is both the most commonly used model and one of the most inaccurate. The Last Click model assigns 100% of revenue

generated to the last customer touchpoint before a purchase, as in the example below.

Last Click

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2nd: Social Media

7th: PPC

5th: Organic Search

6th: Direct

8th: Direct

3rd: Email

4th: Display

Touchpoint

Sound familiar? It probably is. This is the model that

most people use as standard when they start reporting

(often unintentionally), because it’s one where all the

data is instantly available in the format needed. It is

useful because it is simple to set up.

For example, if you’re an eCommerce site using Google

Analytics, all that’s required is to set up a purchase

Event or Goal at the ‘Thank you for your purchase’

page, and then look at the channel acquisition of all

the visitors who got through to those conversions. The

number of users who came from those channels and

went through to purchase is exactly the number of

consumers that channel drove according to Last Click

attribution.

It’s easy to track offline sales too. If you’ve got any sort

of dynamic voucher code generation or call tracking

software, you can generate a code or phone number for

consumers to get touch with you.

However, the model is not without its considerable

drawbacks.

Let’s go back to the explanation of the Last Click

model: 100% of revenue generated is attributed to

the last customer touch point before a purchase.

When you think about this, it is both counterintuitive

and inaccurate. It doesn’t take into account the brand

advertising you conducted to drive awareness, any of

the social media activity you undertook to generate

affinity, or any other activity prior to the point of

sale. That is why the Last Click model often paints an

inaccurate picture; there are a host of other factors

that inform a purchase decision ignored in favour of

simplicity.

Simplicity, in this case, does not equate to accuracy.

check Pros close Cons

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When to use itLast Click is simple to execute but often does not provide an accurate picture... so when can it be used?

One scenario could be if you’re conducting a flash sale on a relatively unheard-of product with a large media spend. In this case

Last Click will probably give you some useful, immediately actionable insights. Or if every single piece of marketing you undertake

is aimed directly at driving a sale, Last Click will again give quick and useful (if not wholly accurate) insights.

However, for most attribution challenges Last Click is too ‘all or nothing’ to deliver valuable business information. In these

situations you need to move on to a slightly more sophisticated model.

By tracking which consumers use which numbers or

codes through your CRM, you can get a quick idea of

which channel drove each visit.


Chapter 4: First Click – Last Click’s

mirror image


What is it?

In layman’s terms, First Click attribution is the polar opposite of Last Click, it attributes 100% of revenue to the first consumer

touchpoint.

For example, if a customer first comes across your brand by clicking on an organic search listing, and then later – from a different

visit – spends £100 on your website, organic search is said to have driven £100 of revenue. As demonstrated in the graph below,

this model disregards any other touchpoints the customer experiences in the run-up to purchase.

Much like Last Click, First Click derives the majority

of its strength from simplicity. It works on the basic

premise that if a user has never heard of you, they can

never buy from you. So however they first heard of you

is the ultimate cause of their spend.

The biggest con of First Click is similar to the biggest

con of Last Click: it deems one interaction – this time

at the beginning rather than the end – to be wholly

responsible for the spend. We know that the customer

journey is more complex than this, and users often

interact with brands many times before purchasing. So

in this respect, First Click’s picture is too inaccurate to

be of business use.

First Click

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8th: Direct

3rd: Email

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When to use itFirst Click comes into play when you have a single channel strategy, i.e. you’re only using one marketing channel to promote your

brand.

In this instance, First Click would be a better place to start than Last Click; imagine launching a brand on Twitter, and a consumer

visiting you directly from that network. A week later, they remember you and return directly to your website to buy a product. In

this case, the First Click model will attribute the sale to Twitter – a fair assumption given that is where the consumer first came

across you. Last Click would attribute this sale to a direct visit, which wouldn’t really be fair, as the direct visit didn’t really do

anything to cause the sale; it was just the medium through which the sale was achieved. The First Click is therefore ‘a more worthy’

method to attribute the revenue.


Chapter 5: Last Non-Direct Click

and similar models


Notes on this chapterThis chapter focuses on the Last Non-Direct Click model – and at the same time we will allude to other models that are similar in

principle but different in activation.

What is it?You will recognise that this model is similar to Last Click, except for cases when the Last Click is a direct visit. In such cases, this

model finds the latest click that isn’t a direct visit and attributes 100% of the revenue to that channel instead. For example:

If the 7th touchpoint was also a direct visit, the model would look at the 6th, and then the 5th etc. until it ‘found’ a touchpoint that

wasn’t a direct visit, which would then receive all the value.

The rationale behind this model is the idea that once a visitor comes directly to your website they have already made the decision

to buy from you, so the cause of that purchase is not the direct visit itself, but the one that pre-empted that direct visit.

There are other, not dissimilar models that work in the same manner, i.e. they suggest that if a certain channel appears at a certain

point in the customer journey, they are either entirely responsible for the conversion, or in no way responsible for the conversion.

Google Analytics has a model called Last AdWords Click (for PPC), which takes whatever the most recent interaction a user had

with AdWords as wholly responsible for the sale. It doesn’t matter if they’d interacted with AdWords prior to the most recent

click, or if they interacted with some, dozens or hundreds of other channels after the most recent AdWords click – the most

recent AdWords click always receives 100% of the credit.

If we slightly adapt our customer journey example to demonstrate this, it would look like this:

Last Non-Direct Click

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2nd: Social Media

7th: PPC

5th: Organic Search

6th: Direct

8th: Direct

3rd: Email

4th: Display

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Last AdWords Click

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(Adwords)

6th: Direct

9th: Email

8th: Social Media

10th: Direct

5th: Organic Search

3rd: Email

4th: PCC

(AdWords)

Touchpoint

Again, there are many models that can be set up in a similar way in order to give all (or no) credit to certain channels at certain

points of the user journey. But they all stem from similar principles, accountability.

By accountability, we mean the ability to judge each

channel according to what it should be doing. If you

know that PPC is the one channel you are using to drive

sales then you can use Last AdWords Click to measure

this. If you know that there is nothing on your website

that is going to increase a user’s inclination to buy, then

Last Non-Direct Click reflects this.

If, for example, you implemented a social media

campaign that encouraged users to buy within a

specific date range, then you could set up a model that

gave 100% credit of any sales in that date range to

any social media touchpoints that occurred during the

campaign. The ability to customise this model to exactly

what activity and goals your business is conducting is its

greatest strength...

...and its greatest weakness. With accountability comes

inherent bias; if you only deem a channel responsible

under certain criteria then you are neglecting the

possibility of it impacting another stage of the

customer journey, or any halo effect it may have. You

are also discounting the impact of other touchpoints in

the customer journey.

In both examples above, and any other model of this

form (all or nothing under certain criteria) there is an

unavoidable bias. In Last Non-Direct Click there is

a natural bias against direct visits, as they can never

receive any credit for the sale, and the last non- direct

touchpoint will always receive all the credit.

Similarly in the Last AdWords Click model there is a

bias towards AdWords. As soon as a user clicks on

an AdWords listing, no other channel has a chance of

receiving the credit.


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When to use itTo state the obvious, the best time to use the Last Non-Direct Click or similar models is simply when the pros outweigh the cons,

and when other options aren’t suitable.

The level of control you are permitted in setting up this type of model, to measure exactly what you want to measure, is of

real benefit. The time to use this model is, therefore, when this benefit outweighs the inherent bias that comes with weighting

everything on an all or nothing model.


Chapter 6: Linear – equal credit to

each touchpoint


What is it?The Linear model is based on a different principle to the First and Last variants. Where those models deem that one part of the

customer journey is solely responsible for the sale, the Linear model states that every step of the customer journey is equally

responsible. It is the democratic attribution model; every touchpoint gets credit for an equal portion of the revenue a customer

spends.

Therefore, in a customer journey where the consumer had five interactions with the brand, each interaction will be credited with

20% of the revenue from that customer. In a journey with eight interactions, as below, each will be credited with 12.5%.

Linear

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1st: Organic Search

2nd: Social Media

7th: PPC

5th: Organic Search

3rd: Email

4th: Display

6th: Direct

8th: Direct

Touchpoint

This highlights another important difference between Linear and First and Last Click models. The Linear model, because it

attributes value to different stages of the customer journey, presents the possibility that one channel can be ‘attributed’ twice.

If you look at the graph above, Organic Search receives 12.5% of the revenue when it appears in both the 1st and 5th touch point.

Likewise, Direct receives credit at both the 6th and 8th position.

Therefore, while each touchpoint receives the same amount of credit for the conversion, different channels can receive very

different amounts of credit in total. In this case, Social Media, Email, Display and PPC each get 12.5% of the credit, while Organic

Search and Direct each get 25%.

Linear recognises that every step of the journey is

important in a customer’s conversion. Linear attribution

Linear attribution does not recognise what a channel,

campaign or activity is trying to achieve. For example,


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means that more than one channel can receive credit

from every purchase and so gives a clearer picture as

to which channels are working best and which are not

working at all.

Linear is also useful because it is a more sophisticated

model but one that is still relatively simple to

understand.

if a campaign receives an extra push of budget, which

could potentially diminish the overall ROI, this isn’t

reflected in the model. Similarly, if a campaign is

intended to drive sales (i.e. the impact should be felt at

the end of the customer journey) but instead generates

awareness (the impact appears at the beginning), Linear

would not recognise this crucial difference and

therefore not demonstrate that the campaign had not

achieved its objective.

When to use itDue to its drawbacks, Linear is perfect when no ‘hero’ or push campaigns in progress. When you are delivering a standard

marketing plan so you can compare how each channel performs on an ‘equal’ playing field. It is a good model to use in many cases

if you are looking to progress away from Last Click, but perhaps not yet ready for a custom model. Because of its simplicity and

fairness, it’s great as a first venture into more sophisticated attribution modelling.


Chapter 7: Positional – location,

location, location


What is it?The Positional model recognises two important factors in a strategy that the other models we have looked at so far do not:

1. The shape of a customer journey

2. The different values of the stages within it

As we know, every part of a customer’s journey to purchase is important. While the familiar path of Awareness > Consideration >

Conversion has become more sophisticated in recent years, the fact that there is a journey, which starts with a potential customer

finding out about a brand, is undeniable.

The Positional model acknowledges and represents this by combining aspects of First Click, Last Click and Linear. Essentially

it says that the first touchpoint and the last touchpoint are worth X% each, and all the other touchpoints in between have the

remaining % divided up evenly among them.

A common set-up of the Positional model is to have the first and the last touchpoint worth 40% each, and the remaining 20%

divided equally amongst the touchpoints in between. For example:

Positional

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2nd: Social Media

7th: PPC

5th: Organic Search

3rd: Email

4th: Display

6th: Direct

8th: Direct

Touchpoint

We have already touched on the benefits of the

Positional model, which recognises that different

stages in a journey should receive credit for different %

of revenue generated. The model gives prominence to

the first and the last stages, those when the customer is

The first issue is the weighting of the percentages. 40%

to the first and last stage of the journey may seem like

a large portion, especially when you consider how little

it leaves for the other stages (particularly when you look

at journeys with many more touchpoints). However, this is


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When to use itSo when do you use this model? A good example is when conducting large scale, global brand campaigns and smaller, local-product

focused campaigns. The intention of these working in tandem is often to generate brand awareness from the large-scale brand

campaign, and product consideration and conversation from the local campaigns. In these situations, Positional attribution is a

great way to measure whether what you think you’re achieving, or what you’re trying to achieve, is what you’re actually getting

from your combined global and national efforts.

This makes it clear that the Organic search touchpoint wasn’t as valuable as we thought. While this was indeed when the

customer first encountered our brand, it was sometime before they came back to us again on social media, and then a long time

before they decided to purchase. In this example it starts to look – at least initially – more like the real catalyst was PPC.

first exposed to the brand and when they converted.

It balances this by recognising that every step in the

customer journey has a role to play, and therefore every

touchpoint receives some credit for the conversion.

So, for the balance of weighting the (potentially) more

important first and last steps of the conversion path

while acknowledging that every step has a part to play,

the Positional model is worthy of consideration.

Positional

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a minor concern as the percentages can be customised,

which we’ll look at in more depth later.

A bigger concern when considering a Positional

attribution model is that, while it takes the shape of

the user journey into account, it does not consider

timescale, at least not in its core design. If you

restructure our example to take into account not just

the different touchpoints on the x-axis, but also the

time between them, then a truer picture would look

something like this (see graph below):

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Chapter 8: Time Decay – not as ominous as it sounds


What is it?Let’s clarify one thing: Time Decay is not the best model. Whilst Time Decay is one of the more sophisticated, in both

implementation and understanding, this alone does not make it the best or the one that everyone should use.

In the Time Decay model the principle is that the closer a touchpoint is to the conversion, the more influence that touchpoint had

on the customer decision.

It is important to stress that ‘closeness’ is based on time, not position in the user journey. This is particularly important when

looking at the example below because the shape of the graph could be very different depending on the time frame over which it

occurs.

To give context to the example, let us say that 24 hours passed between the first touchpoint and the second, 12 hours between

the second and third, and 6 hours between the third and fourth. Then the time keeps halving until only 22 minutes and 30 seconds

passes between the seventh and eighth touch point, which leads to the purchase.

Time Decay

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1st: Organic Search

2nd: Social Media

7th: PPC

8th: Direct

6th: Direct

5th: Organic Search

3rd: Email

4th: Display

Touchpoint

The Time Decay model attempts to represent the

intent of any piece of comms activity to increase a

customer’s willingness to buy and accelerate their

decision to do so. It is a good way to understand which

activities are causing the biggest step-change in your

marketing activity; it gives credit to the touchpoints

Because Time Decay focuses on the timeline, rather

than the shape of a customer journey it can, if not

planned correctly, over-favour the touchpoints most

recent to the purchase. For example, research is an

important stage in many customer journeys. This

research could happen at one time, when the customer


100%

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25%

50%

75%


When to use itWhen you have an holistic, multi-tiered and complimentary communications strategy with each aspect having an intended call

to action that leads to the next step in the journey, Time Decay can give you an accurate picture of whether your strategy is

delivering as intended.

With the right set-up, it can also be a good model for those selling products or services that are long-term considerations as

opposed to impulse buys. The model can show you which of the many different touchpoints are expediting the journey, which

are causing a slow down, and which are causing users to drop off. Here Time Decay can provide a valuable picture of long-term

purchase cycles.

that generate the gradual increases in momentum that

many purchase decisions go through over time and

focuses on touchpoints that are drawing that decision

to a conclusion and converting the sale.

has multiple contacts with the brand. The outcome of

the research could be a decision to purchase, but the

purchase itself could happen several days later. The

time frame between the purchase and the research is

not relevant to the customer. It is an arbitrary period

between deciding to buy and acting on that decision.

Time Decay ‘penalises’ all the important touchpoints

during the research phase simply because of that time

period. In this instance though, the touchpoints most

recent to the purchase are less important that those

during the customer’s research. However, because of

the way Time Decay weights channels, the picture it

presents to senior stakeholders or those not familiar

with the data could be innacurate.


Chapter 9: Customisation – the

better model


The right model for youThe most important factor when looking at attribution modelling is recognising that off-the-shelf models are not the whole

picture. They are a starting point on the path toward identifying the best attribution model for your brand or organisation.

One of the steps on this path is understanding what can be customised, given the right technology and the right set-up. Below we

provide an overview of the different elements within attribution modelling that can be customised and combined to create the

right model for you.

TimeAs touched on in Chapter 8: Time Decay, customising the way a model behaves depending on time can be very important. For

example you could set a rule that, if a customer doesn’t interact with your brand for a week, then that journey is considered over.

If the same customer returns, a new journey is started. Similarly if a customer is exposed to two complimentary touchpoints in

a set space of time, you may want to up-weight the value of one or both because they are shown to be acting in tandem. Setting

different rules based on different time periods is one way to customise an attribution model.

ChannelAs described in Chapter 5: Last Non-Direct Click, different channels have different behaviours and different intentions. You

may therefore want to weight them according to the amount of channel spend, the perceived value of the action it is intended to

motivate, or the amount it appears in different customer journeys.

For example, if you want to quickly look at ROI, and are spending a fraction of the amount on social media than you are on PPC,

then you may chose to down-weight PPC interactions and up-weight the value of social media interactions.

PositionIn Chapter 5: Last Non-Direct Click, we looked at the importance of different channels appearing in different positions on the

customer journey. Does a direct visit to your website that appears in the first stages of the journey have the same value as a direct

visit that occurs in the final stages? You can customise your model to take into account such questions.

Similarly, in Chapter 7: Positional, we examined how important it is to know which positions are the most important to your

customers’ journeys. It is essential to customise positions so they best represent what is right for your brand.

WeightingWe have looked at models that apply different weightings under different criteria: for example Positional depending on different

positions, or Time Decay based on different timelines.

It is possible to customise the different percentage weightings within these models. Should the first engagement be worth slightly


Any combination of the above... and many moreThe end customer action, the campaign you are running, the time of year, which web pages are visited... all of these and more can

be used to tailor an attribution model to your needs and ensure it is as useful as it can be for your business.

All the models we have looked at (and more) are interrelated, and each has its nuances. It is important to have a team who

understand your business, your data, your brand, your needs and your available technology in order to devise the best, pragmatic

solution.

The optimum solution is almost always a combination of everything we have covered. The best attribution projects will consider:

1. The right solution to strive for

2. The best way to get there to continually deliver more ROI on the project as a whole

less in Positional? Should you adjust the credit Time Decay gives to each touchpoint as time from purchase increases? Customising

the weighting you give to each touchpoint in each circumstance is a further opportunity to create an attribution model that makes

sense for your brand.


Chapter 10: A very social media


Demonstrating the value of social mediaBefore concluding, it is worth taking a look at social media, a prime candidate for a case study on the importance of attribution

modelling.

Many Social Media Managers struggle to demonstrate the business impact of their work. They know it’s there, indicated by

improving engagement rates, increased audience sizes, advocacy and more. However, these are still merely indications of a deeper

business success that hides beneath the surface and is difficult to prove.

Social Media Managers know this and understand that social media is primarily an awareness, affinity and retention-increasing

platform, not a channel that focuses on direct selling. But when budget decisions come to be made they find it difficult to justify

why they should have budget because PPC Managers are reaping part of the reward from the awareness and affinity they

generated, which undoubtedly increased that AdWords click through rate (CTR).

Social media and attribution modellingAttribution modelling levels this playing field and proves the business impact that social media has on the bottom line. It allows

Social Media Managers to take credit for the work they are doing by assigning a fiscal value to every action, campaign and

network they manage, and therefore to demonstrate real ROI.

It is tough to justify a campaign that will generate 100,000 Facebook fans if not a single fan from the first 10,000 clicks through

to make a purchase. It is easier to do this when you can prove that each of those fans added £1 to the bottom line; it just appeared

further up the conversion funnel than had previously been identified. All of a sudden that Facebook campaign seems to make a lot

more business sense.


Conclusion

PicturesReading, understanding and implementing the suggestions in this white paper is a first step. The most useful attribution models,

those that hit the sweet spot of being the most accurate and well used, are bespoke implementations that reflect detailed

knowledge of a brand and its communication strategy.

We hope we have demonstrated the possibilities that implementing an attribution model offers, and why it’s important to ensure

that the model presents an accurate picture of customer behaviour.

The question always arises as to whether these pictures will be perfect, and the honest answer to this question is no. No picture of

communication attribution is perfect, and anyone who claims otherwise is peddling snake oil. There is always the possibility that

customers will swap devices, swap browsers, deny tracking cookies and so on. It is difficult to circumvent one, let alone all of these

and as a result attribution will always present an imperfect picture. However, this picture is still a significantly more accurate and

useful one than traditional reporting allows for.

We have only scratched the surface, there are valuable methods that include offline communication and customer engagements

in your attribution model to give an even fuller picture. This can include TV, print, DM, telesales and more. So the future is bright

for those who invest in attribution modelling now, and use it to optimise their marketing spend in future.

Where next?Some may focus on the bad news after reading through this paper, to recognise how far away we are from the perfect attribution

model. This would be to deliver false worry, no optimum model is implemented overnight: it is a process of small steps towards a

greater goal. With each step resulting in small learnings that can deliver big wins.

There is always a first step you can take with the information you have available. Just having a data strategist look at the data your

digital marketing activities generate, in light of the business return you have actually delivered, will reap wonders in terms of costs

that can be saved, profits increased, and budgets efficiently allocated.

It is possible to get to the truth about how your digital marketing activity is impacting your bottom line, and deliver valuable and

appreciated reporting as a result. Don’t report your data to suit your strategy, design your strategy in response to data.


Get in touchTo find out more about how Bloom can help define and implement the right attribution model for your business speak to:

John Murphy

Head of Multichannel

+ 44 (0) 1273 732 626

[email protected]

@JohnMur3

About the author John is our Head of Planning here at Bloom. He lives and breathes digital – from social to search, PoS to Python and everything in

between, John has worked with all types of digital communication and is always up to date with the latest industry changes.

A numbers geek at heart, John also prides himself on making sure everything he and Bloom does is grounded in numbers and leads

to numbers; ensuring work is based on provable insights to maximise success and leads to measurable results to demonstrate

actual business impact.

By combining digital knowledge with data-driven intelligence, John has lead and worked on projects that have won awards

including DMAs, Marketing Week Engage Awards, BiMAs and more.

John’s shamelessly paraphrased motto is ‘head in the clouds, feet on the ground’ – he believes that the best ideas are those which

are over-ambitious but not unachievable, and that all work is only as good as the action or change it drives.


@bloomworldwide

www.bloomworldwide.com

[email protected]

Thanks for reading

digital marketing roi - an introduction to attribution modelling

Data & Analytics