← More Posts

 

Written on 06/12/18 5:08 PM

 

With only 23% of marketers confident in their ability to use data to optimize customer experience, and an overwhelming volume of data at their disposal, how can you develop a successful strategy? According to Altimeter’s customer research, there are four key steps to leveraging data for an optimal customer experience:

1. Focus on one customer experience category for your objective.

2. Prioritize only the data points you need for customer success.

3. Use a data management platform to view data holistically.

4. Create centralized data insights and experience delivery teams.

Want to learn more? Download the complete report, Creating a Data-Driven Strategy for Customer Experience, here.

 

by Jennifer Wiza

Attribution Modeling – Holy Grail or …

Attribution. It’s the word on every marketer’s lips, and it’s impacting how media budgets are developed and optimized. But in today’s multi-channel environment, attribution “science” may not be telling the whole story. While attribution modeling provides increased visibility into a customer’s journey, models often tell only part of the story – on-line conversions and channels. If your data shows that a significant portion of conversions have long, multi-step paths – meaning customers are engaging across multiple channels – you may have an attribution gap.

Attribution – On-line-to-off-line

If you don’t understand how online channels impact on offline revenue, you’re only seeing part of the story. Only looking at digital conversions and revenue fails to take into account the effect on offline sales and in-store visits. Of course, one way to address this is with unique promotion codes by channel to fill the gaps in the story, which allows you to track conversion. Google’s “In-Store Visits” metric uses multiple signals to determine online/offline impact, including Google Maps data, WiFi, GPS and more to create in-store visit estimates, but this only applies to the million opted-in users.

Platforms that leverage mobile device data are also a step in the right direction, although they don’t track a specific user’s activity.

Attribution – Cross-device

The proliferation of devices has created another attribution challenge – measuring consumer behavior and engagement across devices and screens. The migration of search away from taps on the screen and toward voice-recognition tools will only make this more difficult. Although some companies can begin to make headway through multiple screen and device logins, it remains an area of opportunity.

Attribution modeling will only continue to improve as tools emerge to support a holistic approach to campaigns – across channels and across devices. Working with an attribution model that supports holistic marketing campaigns and efforts while avoiding simplistic “first- or last-click” approaches will help ensure multi-channel campaign optimization. Tracking the interplay of on- and off-line behavior and activity isn’t easy, but it can be addressed with unique promotional codes tying back to the individual channel. Regardless of attribution model, challenges and opportunities remain for improvement as we seek to understand consumer behavior and invest in the areas of greatest value.

Analytics is embedded in everything today’s marketers do. This not only requires a cultural shift that impacts how marketing teams work together as much as it impacts what they do. An analytical marketing approach requires that teams act differently, as much as it demands that they think differently based upon what data is telling them.

In this Harvard Business Review article, Adele Sweetwood, the Senior Vice President of Global Marketing and Shared Services at SAS, looks at three approaches to build an analytical culture. The idea of a “common analytical culture” helps organizations develop the ability to make adjustments on the fly, creating the opportunity to implement real-time changes and empowering the marketing [are we missing a word here? Team? Group?] to respond more quickly.  She looks at three ways that teams in an analytical culture must think differently.

1. Use data to change the status quo – Teams need to think differently about marketing because the availability of new data and metrics allow them to be more effective and enable them to identify new approaches
2. Use stories to convey data insights – Teams can ask what-if questions to uncover other stories it can begin to tell, enabling teams to shift from being reactive to proactive, creating a culture focused on the future, rather than having one weighed down by the past.
3. Use different metrics – In the past, metrics provided something to react to, but today reacting to metrics isn’t enough. Customers now have greater expectations about what they expect us to know as marketers and how we interact with them.

Learn more about how an analytics mindset changes marketing culture, read the full article here.

 

What is Programmatic Advertising? Programmatic is the automation of buying and selling digital advertising inventory, including real-time bidding (RTB), that has seen tremendous growth over the past five years. It has started to transform how we buy and sell ad inventory. While RTB has historically been associated with remnant inventory, this technology is now increasingly being applied to a wider range of inventory. There has been confusion in the marketplace over terminology with a number of terms being used interchangeably such as: “programmatic,” “programmatic direct,” “programmatic premium,” “programmatic guaranteed,” and “automation”. Many definitions abound and they vary from site to site and from partner to partner. Additionally, marketers are bombarded with a lot of acronyms when referring to Programmatic, for example RTB, DSP, DMP, SSP, and many more. We will attempt to decipher and provide definitions for many of these key terms.

In simplistic terms, another word for Programmatic is Audience Buying because that this is essentially what advertisers are purchasing:

instead of placements, they are purchasing Audiences regardless of where they may be browsing or surfing. The inventory is bought using algorithms, AI (artificial intelligence) and automated trading/bidding systems. At the core of Programmatic is the Ad Exchanges; they aggregate digital ad inventory from millions of sites and operate very much like a Stock Exchange. We’ll explore that in a later section.

The below graphic gives on overview of how programmatic is structured from the media agency side as well as the publisher side. Programmatic sits in the middle and makes decisions in real time as to how the inventory is bought and sold.

Why do we need Programmatic?

With programmatic buying, advertisers have access to vast amounts of inventory, data, and targeting options. According to eMarketer, by 2017 83% of all display ad buys will be purchased programmatically. Magna Global predicts that US programmatic ad spending will hit $17 Billion by 2017.

Programmatic buying allows advertisers to target audiences in a multitude of different ways, below are the main options for targeting display, mobile or video ads:

In the future, most buying will be done via programmatic; not only for display ads but also for video, TV, audio, social and native. Buying in this manner actually saves money because of the efficiencies brought about by automation. However, costs can quickly escalate the more vendors and technology companies that enter into the mix. Each will get a cut of costs which can quickly add up.

The advantages are:

• Economic Efficiency

• Targeting

• Organizational Efficiency

• Measurement

• Transparency

 

How does it work?

At the core of Programmatic is the Ad Exchange. Similar to the stock market, ad inventory on the Exchange is placed into a bid auction system where advertisers can bid on ads based on location, demographics, psychographics and a range of other criteria. The inventory options that are available go far beyond display ads including: Video, Mobile, Native, Social and Audio.

The graphic below demonstrates how all of these platforms and systems work together in a complex ecosystem that operates within milliseconds of an ad being delivered to a users screen. Both agencies and publishers are feeding in buys and inventory on either side. In the middle stands a system of Trading Desks (owned by agency holding companies), DSP’s (Demand Side Platforms), Ad Exchanges, Data Providers and Management Platforms (1st party and 3rd party), and SSP’s (Supply Side Platforms).

 

Definitions:

Trading Desk: large agency holding companies that have their own programmatic buyers that purchase directly from the Exchanges for their list of clients.

DSP (Demand Side Platform): enables advertisers to purchase ad inventory via RTB exchanges (examples are MediaMath, Turn, Invite Media, The Trade Desk)

Ad Exchange: a digital marketplace that enables advertisers and publishers to buy and sell advertising space, often through real-time auctions (Doubleclick, AppNexus, OpenX)

SSP (Supply Side Platform): a technology platform that enables web publishers to manage their advertising space inventory, fill it with ads, and receive revenue

DMP (Data Management Platform): provides the function of data collection, translation, classification, indexing and storage. In simple terms the ‘plumbing’ part of data-driven marketing online. (Oracle BlueKai, Neustar, Aggregate Knowledge)

Data Usage:

Programmatic buying allows the inclusion of many data sources to inform targeting and optimization decisions. It allows the buyer to show one ad impression to one anonymous viewer in one context. In the current programmatic landscape, the most common data used is leveraged on the buy side. Buyers layer both third-party data, as well as advertiser first-party data, onto campaigns. In addition, some publishers offer their first-party data.

Protecting against Fraud

Industry research has shown that an average of 55% of all digital display ads are not seen at all. This could be due to many factors: ad is below-the-fold and the user did not see it, fraudulent non-human traffic that comes through from bots or other computer programs.

Moving toward Viewability is RPM’s #1 priority moving forward and we are setting up systems to ensure that all of our advertisers are getting the highest percent of viewable impressions. Verification companies including 3rd party ad servers have viewability measurement built in to measure whether an ad is viewable or not on desktops or PCs. Mobile measurement will follow shortly but is not ready for primetime.

More and more high quality inventory is being made available programmatically like private marketplaces and publisher direct. By accessing this inventory, we can improve the quality of our ad placements and also improve viewability.

Programmatic Vendors

As you can see by the below Lumascape chart, there are an enormous number of players in the Ad Tech space. More come to market every day and also get acquired by other companies or change business models. Keeping up with the rate of change is very challenging, however, RPM keeps abreast of these changes by attending industry events, researching technologies and scheduling regular vendor meetings.

How is it Measured?

Programmatic buying can be purchased in different ways depending on campaigns goals. Below are the most common goal and cost structures:

 

• Awareness: CPM or Cost-per-Thousand (used most frequently)

• Performance: CTR (click-through rate), CPA (cost-per-acquisition), CPL (cost-per-lead), ROI

• Viewability metrics by the 3MS (MRC, IAB, ANA and 4A’s) have established the following measurement standards to assess whether an ad is viewable:

• Display: 50% of ad pixels must be viewable on desktop/PC for 1 continuous second

• Video: 50% of ad pixels must be viewable on desktop/PC for 2 continuous seconds

• Mobile: Viewable Impressions guidelines are currently being decided upon

Recommendation

Due to the enormous amount of inventory and opportunities Programmatic has to offer, it is an area for growth and exploration for all PNG properties. RPM is already working with Programmatic partners and has begun testing these vendors to determine reliability, volume and performance. We will continue to test new DSP partners to determine which ones fit our needs and comply with our quality standards. RPM is researching future opportunities for establishing its own trading desk using the latest technology with 100% transparency while also ensuring the highest quality inventory.

Next Steps

• Viewability Approach

• Determine and test new Programmatic partners

• Share goals and objectives with new partner

• Implementation

• Shared Analytics

• Evaluation