What are we talking about?

Buyer 2.0

No Clue !!!

Scary

Some Important Questions

What has gone terribly wrong with “Marketing”? How will Marketing provide an answer to “User”

acquisition or “revenue” generated per user? What will be the future marketing vehicles and

Advertising Formats? How will “Marketing” success (or ROMI) be

measured to give excellent returns in Marketing investments?

Problems with Marketing Today

Most concepts practised and learnt today are seeded in the early industrial-revolution era

Shortcuts to Marketing success, like – Advertising Pulsing, mass-media bombardment, spamming techniques, etc are the hallmark of standard practices

Missed the bus on innovation in communication platforms (eg. Social); no available research in future of marketing effectiveness and measurability; ignored Buyer2.0 progress

Have maintained the failed status-quo to become a huge cost center for organizations

But can we really live without Marketing?

NO

My Research

Understanding User Acquisition through Online Advertising Models and Integrated Marketing systems

Soumik Ganguly

Objectives

Provide Analysis and then a Formula to explain User Acquisition scientifically

Prove that Advertising Pulsing is Wrong, and provide clue to Super-linearity in Advertising/Marketing returns

Provide a clue to Future marketing platforms and formats that will maximize user acquisition

Provide a scientific way to integrate marketing and then fix measurability

We start at the basic building blocks of Advertising logic

Two parts of the Ad world dichotomy

Intent

Demographic

Analyzing various Ad Campaigns

Business Function of (i/d)

Pulsing Demand (Qgt) Purchasing Power

Deals f(d) Beta Beta Beta

Mobile Phones f(d) Alpha Beta Beta

Entertainment f(d) Beta Beta Beta

Insurance f(i) Alpha Beta Alpha

Healthcare f(i) Alpha Beta Alpha

Sports f(i) Beta Beta Beta

Here, “i”=Intent and “d”= Demographics

Alpha = Low; Beta = High

I have considered that all Ad platforms can be classified by the functions of intentions and demographics. "Action" is something that is the ideal return on investment for all advertisers.

Analysis of over 20 campaigns each domain over a period of 1 yr

The Math – Defining Engagement

Now let us consider that for most businesses, there will be 'g' firms that would be the main advertisers and any additions post those firms into the system will not affect the system behavior drastically.

For a specific time 't', there is a requirement for Engagement to happen so that the final "ACTION" is taken - which is nothing else but the buy decision.

We can therefore say:E i (Engagement is Directly proportional to Intent) E = i x D [Considering D = Demographics as a constant]

For all firms "g", at time "t", the given equation can take a form of:E

gt = i

gt x D

t (1)

The Math – Defining User Acquisition

User Acquisition, Ua= Egt x At (Product of Engagement and Action)

wherein, User Acquisition is a multiplicative product of Engagement over a campaign/channel and the Action taken due to that engagement;

Substituting values from Equation 1,

= (igt x Dt) x At (2)

Action can be defined by the purchasing power multiplied by the demand of the product/service at a given point in time. Therefore, simplifying

Action -> At = Qgt x Ppt (3)

The Math – Final User Acquisition Formula

Advertising improves reach, visibility and presence for a product at a given time, adding to the demand function. Goodwill for the brand and the price factors too add on to the demand function for a specific product/service. Therefore;

Demand Qgt

= Qg (W

t, P

t, Ad

t) (4)

[wherein Demand in a function of goodwill(W), price (P), and advertising(Ad)]

Therefore, At= Qg(Wt, Pt, Adt) x Ppt (5)

Now, Ua = igt x Dt x Qg(Wt, Pt, Adt) x Ppt

Conclusion:

- Advertising continuity has a direct impact on the user acquisition formula

- Intent is an important factor of engagement affecting user acquisition

Improving the Demand side of the Equation

Egt

= igt

x Dt

Ua= Egt x At

Improving the Demand side of the Equation

Early 2000s

Current Work

The Current HopesFor Marketers

Important conclusions Ad-pulsing is an incorrect strategy The future of advertisement has to include options

providing opportunity for High Engagement and Action at the same time.

Super-linearity in User acquisition and advertising returns will be possible if there are large number of Human Interactions (Engagement) in the system

Measurability in Marketing(and how to solve it)

Case Study on Integrated Marketing using Bayes Theorem

Involves Pagalguy.com and Management Institutions as two distinct participants

Pagalguy.com – Online Marketing PlatformManagement Institutions - Advertisers

Case Study of a B-schoolProblem Statement:

Every year, b-schools are faced with the biggest challenge of strategically choosing communication channels for their Admission purposes, trying to ensure that they get it RIGHT.

They measure the results that come from each marketing channel they choose rather than a multi-channel strategy and measurement. They use certain channels incorrectly, without completely understanding the characteristic consumption pattern of their Applicants in that channel.

The Ideal Marketing Mix

The Math behind MadnessThe given Marketing Mix means that the bschool is using 6 different but

integrated channels for its marketing program. Let's consider that

Result = ʄn(Action, Engagement)

Now, according to integrated marketing assumptions, the action and engagement can happen in two different channels at a given point in time "t".

Which means that the number “(Action,Engagement)” possibilities would be:

6P2 (permutation) = 30 such sets contributing to the Result from the marketing campaign

Example:

Rt = (A1,E1) = (Pagalguy, Database Calling)

R(t+1) = (A2,E2) = (Database Calling, Pagalguy)

How to Choose a Marketing Channel?

It is impossible to attribute specific inputs to specific channels for results, the best can we can predict is the probability of engagement of a particular platform at a certain time for a result "R".

Mathematically, this would mean-

P(PG) = Probability of student engaging with Pagalguy.com

P(C) = Probability of student engaging over a call

R = Result from the overall marketing system

We want to identify

“What will be the probability of engagement on Pagalguy, when there is a Result from the marketing system?”

This can be denoted as - P(PG | R)

Contd...

Using Bayes Theorem:

P(PG | R) = [P(PG) * P(R | PG)] / [ [P(PG) * P(R | PG)] X [P(C) * P(R | C)] ]

First, calculate: the probability of a result for engagement happening in PG as well as calls.

P(R | PG) = Time x Activity x (1/Total number of options at a given time) = 4 x 5 x (1/50) [Considering 4 hours total time, 5 pages viewed each time, and 50 B-schools as option during his visits] = 0.2

P(R | C) = 0.1 x 10 x (1/100) [Considering 0.1 hours call time, 10 calls, and 100 bschools calling] = 0.01

Now, The P(PG | R) = [0.4 x 0.2] / [ [0.4 x 0.2] + [0.2 x 0.01] ]

= 0.08/0.082 = 0.97

or 97% probability of Pagalguy engagement when Result is "R" (i.e. A conversion happens) from the marketing system.

Let's Discuss

Reach me at:twitter.com/soumik0102

www.accidentalsalesguy.blogspot.comwww.mytakeonbschools.blogspot.comEmail – soumik.ganguly@pagalguy.com