Programmatic Advertising from a Data Scientist s Perspective

Similar documents
Transcription:

Programmatic Advertising from a Data Scientist s Perspective OMK, 17th August 2017, Bern Gergely Kalmár Senior Consultant Digital Analytics Webrepublic AG 1

Programmatic Advertising What s in it for a Data Scientist? Data points. Lots of them. 2

Agenda 1. Introduction 2. The Programmatic Data Landscape 3. A Simple Analysis: Audience Clustering 4. An Advanced Analysis: Marketing Mix Optimization 5. Summary & Outlook 3

Introduction 4

- - Performance Marketing, Online Advertising, Digital Analytics 120 clients, national and international 130 employees 12 languages spoken in-house dedicated - digital analytics team - software engineering - graphics department iab Digital Agency of The Year 2017 5

What is a programmatic campaign? For the current session we define it as follows: A programmatic campaign is a multi-channel online campaign that has a central server that is able to track all ad impressions and clicks for all involved channels, as well as specific online conversions. Programmatic campaigns may (but not necessarily) as well: - use a platform for buying display placements that are then served programmatically, - use a central ad server hosting the display creatives. 6

The Programmatic Data Landscape 7

Customer Journey Tracking 8

Customer Journey Tracking Actually female ity l in rea User bought the product because her mother asked to User deleted cookies Sad data scientist cost data Cost data unavailable Happened on mobile 9

The Programmatic Data Landscape Behavioral data Impression data Your website Click data Audience data Cost data DSP Ad server Display campaigns 10

The Programmatic Data Landscape Behavioral data Impression data Your website Click data Tracking Audience data Cost data DSP Ad server Display campaigns Media buying 11

The Programmatic Data Landscape Behavioral data Impression data Your website Click data Tracking Audience data Sync Cost data DSP Ad server Display campaigns Media buying 12

The Programmatic Data Landscape Behavioral data Impression data Important! Your website Click data Audience data Cost data DSP Ad server Display campaigns 13

Web Analytics Tool-Based Attribution 14

Web Analytics Tool-Based Attribution Search gets all the credit Impressions are invisible 15

Ad Server-Based Attribution Ad server 16

Ad Server-Based Attribution Both the display and search channels may get credit Ad server 17

Fun fact: view-through conversions can account for up to 80% of all conversions on display (banner) campaigns. Source: a campaign executed in May-June 2017 for a global brand; measured view-through conversion contribution was 80% in CH, 63% in USA, 44% in DE. 18

Section Summary - Use an ad server to enable centralized, impression-level tracking especially when you have display or social media campaigns. - Do not be surprised if your display or social media campaigns do not seem to perform well in your web analytics tool. - Always remember: the fact that someone has clicked on your ad and converted does not mean that the person converted because of your ad. 19

A Simple Analysis: Audience Clustering 20

The Programmatic Data Landscape Behavioral data Impression data Your website Click data Audience data Cost data DSP Ad server Display campaigns 21

Audience Clustering & Optimization 1. Identify. 2. Focus. 22

Audience Clustering & Optimization Step 1. Identify the CPA range where most of your audiences lie. Step 2. Focus on high-volume, low-cpa audience clusters. High-performance niche audiences Low-performance niche audiences 23

Audience Clustering & Optimization Step 1. Identify the CPA range where most of your audiences lie. Step 2. Focus on high-volume, low-cpa audience clusters. Optimization potential 24

Audience Clustering & Optimization Males Females 25

Audience Clustering & Optimization Males News junkies Females Cooking enthusiasts Celebrity news 26

Audience Clustering & Optimization Males News junkies Females Cooking enthusiasts Celebrity news Autos & vehicles Luxury travelers Land Rover (in-market) 27

Section Summary - When doing audience optimization focus on high-volume, low-cpa audiences. - Sorting the audiences by lowest CPA may not help much, because the ones with the highest efficiency will be typically small niches. - It is usually helpful to analyze remarketing audiences separately from other audiences. 28

An Advanced Analysis: Marketing Mix Optimization 29

Marketing Mix Optimization Digital marketing investments can be changed in a matter of seconds. The investments can be shifted from less-performing channels to better performing ones (manual). The overall investment can be adjusted depending on the company s sales performance in near real time. Key Questions: 1. How much performance boost can we expect from our budget optimization efforts? 2. How can we select the optimal budget for our digital marketing channels? 30

Problem Definition The overall number of conversions (or the conversion value if available) needs to be maximized: Assumption: all marketing channels are independent We need a model to predict the number of conversions for a given budget for each marketing channel where Ci is the number of conversions for channel i, Bi is the budget for channel i and S is the overall digital marketing budget. 31

Budget Curves The core problem to solve is finding the relationship between the marketing budget and the number of conversions (including view-through) for a given marketing channel. An example of a possible model for Google AdWords 32

Summary & Outlook - Use an ad server to enable centralized, impression-level tracking especially when you have display or social media campaigns. - High-level audience clustering can be done with relative ease, and is often times included in Data Management Platforms (DMPs). - Marketing mix optimization needs advanced predictive models with high accuracy and thus specific knowledge or (typically expensive) tools. - An appropriate system is capable of tracking campaigns on a micro-level, however, campaign management typically happens on a macro-level. The current optimization approaches are therefore quite rudimentary. 33

Contact: +41 44 542 45 11 gergely.kalmar@webrepublic.com Let s it happen. Thankmake you for your Thank you. attention. 34