I. Setting the Stage
We’ve built quite a few consumer, enterprise, and industrial-grade technologies over the last decade. From inventing novel technologies to basic bug-fix blocking and tackling, software is always software and business is always business.
When you think about Emerging Tech, you probably think rocket ships and autonomous robotics, next-gen materials like graphene and mxene, VR/AR, and of course biologic intelligence. But what you probably don’t spend much time considering is state of the art marketing and advertising technology.
But you should. Because the massive amount of capital that flows through these systems every year is astounding:
Google is straight killin’ it. But hold your horses. Did you know that marketing budgets are now bigger than advertising? We’re going to pause for effect…marketing is bigger than advertising.
There are now 5,000 MarTech companies in existence up from a paltry 150 in 2011. That’s insane growth, mostly due to the SAAS and cloud business models. You might have seen this market map a million times already, but here it is again for effect:
And now P&G, the world’s biggest advertiser, is slashing their own ad budgets, trying to reduce waste against bots and take a more generalized approach to Facebook, all while hypertargeting is picking up steam across the rest of the industry. But you might be asking yourself, “how does this massive machine work at the highest levels?” and “what’s the difference between a DMP and DSP?”.
Why so many acronyms! How does this all work?
That’s what we’re here for.
II. MarTech Cheat Sheet
We first need to get you up to speed with some of the terminology. So we created a glossary of terms to help you break into this death-defying world of wonder.
Don’t worry, though, nobody is using your Personally Identifiable Information (PII). It’s against the law and privacy is taken very seriously. It all happens through browser cookies, website tags, IDs, and anonymization. All that’s left is demographic and psychographic data where people are grouped together in certain buckets called Segments and then fed into advertising software to (hopefully) show you something you’re already interested in.
Find out how this is all done at the highest levels of business below.
DMP: Data Management Platform
- Data warehouse to store and analyze data
- Onboard data, segment it, and activate it on DSPs
- Optimize media buys and ad campaigns
DSP: Demand Side Platform
- Buy advertising based on segment data from the DMP
- Signal: smallest data units (key-value pairs like gender = female)
- Trait: combination of one or more Signals using Boolean expressions (gender = female AND age = 18–24). A trait only collects data.
- Segment: users who share a common set of attributes. A segment sends data and is used for 1) reporting and analytics, 2) Audience activation in other platforms (DSP).
Data Onboarding Process
- Companies upload offline 1st party data to platform (e.g., Liveramp)
- Platform anonymizes data to remove PII (personally identifiable data)
- Offline data is matched with online data (e.g., using IDs, emails, etc); includes additional data: user ID, cookie ID from 3rd party DSP
1st party data (most valuable)
- Offline: name, address, phone number, email, date of birth, transaction data, CRM data
- Online: from your own website (tracking cookies), emails (1x1 pixel), social media, mobile apps
3rd party data
- Purchase it
- from places like Liveramp: consolidates and anonymatizes PII data from various sources, devices, etc; true omnichannel
2nd party data
- New, less well known
- Purchase 1st party data from someone else
Onboarding Platforms: brings offline data into DMP
Connects online data with offline data
- Ingest, anonymizing, matching, distributing customer data
- Offline data: name, email, address, phone number, transaction data
- Offline data to match to digital IDs like Twitter or Facebook
- Anonymizing PII (personally identifiable information)
- Reach customers with more relevant marketing messages
- DMPs only have cookies
- Enables building offline segments
- Moves data between major marketing apps
- Onboard data from core CRM to Google, 3 ad networks, Facebooks and Dish TV
- DMP’s are typically limited, 2-dimensional analysis overlap one segment with another to see overlap heat map
- Use Omniture (adobe analytics) instead
- Look at performance of campaign in DMP, with segments set up in advance, if using Adobe Analytics can slice and dice after the fact like Heap Analytics
Data Source Gotchas
- Can always capture customer/user action
- Can’t always capture exposure
- Outlook and Gmail block DMP pixel
- Google Search: can’t see what was searched for, but can capture click
- Google Display Network: does not allow tracking pixels, except if DSP is linked to DMP to purchase ad inventory
- Facebook: does not allow pixel tracking in media (can collect click/user agent)
- Browsers block 3rd party cookies: Safari desktop and iOS 10 (can do 1st party tags of course)
- DoubleClick Campaign Manager (DCM) tracking: Adobe pixel in DoubleClick platform, implemented everywhere media is running in 3rd party space
- Programmatic Platform / trade desk: AOL (AdapTV), Adobe Advertising (TubeMogul) feeds data back into Audience Manager automatically
- Message: creative
- Person: psychographic and demographic segments, personalized targeting
- Medium: google and Facebook ads, emails, billboards, Alexa
Questions for Customers
- What’s the product / campaign?
- What are the goals?
- Who are you trying to reach?
- Do we have the ability to target them today (look at traits currently in DMP)
- Are you using 1st party data?
- Consistency across different mediums: email, website banner, ad creative (cross-channel synchronization)
- Run A/B tests?
- Are you sending current customers marketing for a product they already own (ie., wasted money)
- Diminishing returns (are you sending the same person the same message hundreds of times? What’s the right level?
- How many different DSPs or Analytics providers are you using? Separate from DMP? Consolidate to trade desk
- Adaptv, Tubemogul
- Do you have all the tools necessary? Assets, data sources, do they talk to one another?
- Marketing Technology Architecture: can we get the data necessary to track campaign performance?
- IBM Core Metrics vs Adobe Analytics
- Where are the gaps to being more efficient with marketing spend?
- Audience suppression if targeting the same person too many times (i.e., more than 20) or if it’s reaching too many bots (IVT = invalid traffic, NHT = non-human traffic)
III. Brand Case Studies
We’ve also pulled together a spreadsheet showing case studies of major brands using DMPs to great effect. We’re still adding to the database, but you can see their industry, size, DMP of choice, goals, strategy, and results.
As you might expect, there are consulting teams hired by these big F500 firms to help spend their money wisely. It exists as a counter balance and check against the agency side of the business that creates the content and often does the purchasing of ads, programmatic or otherwise.
We hope you find this valuable. Reach out if you need help.