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AffinityAnswers

Niche Gaming Audiences using ActivationPlanner

By | Blog

Gaming has become a more accepted part of popular culture and has seen a massive expansion in the number of players. Up to 65% of American households play video or computer games every year.

The video gamer is no more a nerdy young male. A study by ESA indicates that women make up 40% of the gamer population. While 27% of game players are under 18, 26% are 50 years or older! Additionally, video gamers have genre and game preferences.  As the profile of a video gamer turns from a stereo-typical age & gender to sophisticated and unique traits, segmenting and targeting such audiences becomes a challenge.

Say you are a gaming company looking to target audiences for a new game in the MOBA genre, and you would also like to reach audiences considering Racing & Shooter games. One approach is to find data partners that have gaming purchase behaviors across these genres and run a look-alike-model.   Cost of purchase behaviors would typically be high and it would get diluted by the look-alike-model.

Affinity Answers audiences are act-alike, i.e. audiences that act similar to MOBA, Racing & Shooter game players.  Social media is a great place to find such similar audiences, and Affinity Answers brings these to the programmatic ecosystem. The recently launched ActivationPlanner provides such act-alike audiences, audience characteristics that you can pick and provision for targeting on your platform of choice.

The screenshot below shows how an audience interested in ‘Non-Violent Video Games’ can be defined using ActivationPlanner.

Once defined, you can get a reach estimation for the audience from Oracle Data Cloud and/or LiveRamp. You can even “build the audience” with just a click.

The current version of ActivationPlanner includes pre-packaged audience definitions for ‘Beauty & Cosmetics’ and ‘Gaming & E-sports’ verticals that can be combined with Lifestyles. Next available audiences via ActivationPlanner are from Automotive —stay tuned!

To schedule your demo and free trial of ActivationPlanner, please email us at audiences@affinityanswers.com.

ActivationPlanner Audience Definition screen

Niche Programmatic Audiences at Scale via ActivationPlanner

By | Blog

With the plethora of audience insights & segmentation tools available for audience data, there’s an overwhelming feeling of tool overload. All these tools seem to be missing one big element: context of your client’s targeting needs.

Let’s walk through an example. A typical client brief is as follows:

Request: Reach women who lead healthy lifestyles and care about the environment. They believe the beauty products they purchase should be a direct reflection of the overall lifestyle they lead. They are minimalists, who believe that when it comes to makeup – less is more. Increase category share by targeting women interested in competitive brands.

With the audience tools you have at your disposal, it’s up to you to search, discover and combine the taxonomy segments to potentially find the best suited audience for this client brief. We feel your pain!

To ameliorate this, we’ve built ActivationPlanner which puts you in control for such a brief. For a request like the above, we have pre-packaged audience characteristics which satisfy your client’s targeting needs. The screenshot below shows how this audience can be defined.

Post defining the audience, with only one click you can obtain an Estimate of Reach via Oracle Data Cloud and/or Liveramp marketplaces. The near real-time nature of the tool helps you respond to your RFP and close more deals. The tool also allows you to provision the audience to your DSP of choice.

We’re launching this within the context of one vertical: Beauty & Cosmetics. Be on the lookout for the next vertical: Gaming & E-sports.

If you’d like a demo and test-drive of ActivationPlanner, email us at audiences@affinityanswers.com.

Mobile Audiences via Adsquare

By | Blog

Affinity Answers has partnered with Mobile Data Exchange, Adsquare, to deliver US based mobile only audiences.  These audiences are available via Adsquare’s Audience Management Platform (AMP).  In addition, these audiences will also available on leading DSPs like Google DBM, The Trade Desk, MediaMath, Adform, to name a few.  Below are a few screen shots of our Taxonomy on AMP.

Taxonomy verticals, with coverage on Consumer Brands and Media & Entertainment.

 

                                              

Expanse of TV/VOD Taxonomy coverage                     ~7.7MM Device IDs are available to be Activated for the Netflix show, Stranger Things

Affinity Answers is a leading data provider with a unique approach to identifying audiences.  Our AI-based Recommender identifies audiences in mid-lower funnel of their purchase journey.  Audiences that are in consideration stage for Organic Beauty products, a Gaming console, Camping gear and many more.  For Media & Entertainment vertical, our AI-based Recommender identifies audiences that are highly likely to view a specific TV show, movie, attend a music concert/festival, sports event, listen to a specific artist, etc.

View our case studies here.  Reach us at audiences@affinityanswers.com for more information or if you’re unable to find these audiences on your programmatic platform.

Audience Enrichment Comes in Many Flavors

By | Blog

The idea of Audience Enrichment has been around for decades in the list-rental business, but it means much more in the offline/online world of data today.

It is no longer theory or even past tense; It is reality. Technology rolls on and affects all industries and in turn, how we do our jobs. In marketing & media, you can trace a path from direct marketing analytics to digital marketing analytics to the current machine learning-led predictive analytics trends we see shaping business operations today.

The progression has been led by advances in computing power, storage capacity, and advances in data science.

As prescient as Gordon Moore was when he made his 1965 prediction about the future of computing power, the announcement of the Netflix Prize in 2006 generated innovation & collaboration around applications of big data, the likes of which had not previously been seen in marketing analytics.

Even with the advances in data science, when it comes to data, more is not necessarily better. Marketers understandably want to make the best use of their own data, regardless of the quantity or quality of third-party data availability. So how can you increase the value of your data?

There are opportunities for marketers to strengthen the value of their data through various approaches, but it is important to consider the trade-offs associated with each type of enrichment.

  1. List Appends via Direct Match:

A deterministic solution. Additional variables are appended to your user-level data to create more descriptive profiles of users. These include attributes such as demographics, auto registrations, lifestyle, and category interest data. Many of the sources used are publically available and can be enrich via deterministic matches.

Trade-Offs

  • Massive scale can be achieved
  • Match is typically done against a total US adult file of 240mm records with physical addresses
  • Offline data is the primary source, which is not refreshed as frequently as online data
  • Demographic and lifestyle data is widely available and different sources do not always match each other
  • Data must be on-boarded to digital ID’s in order to make actionable for digital campaigns
  1. Digital Matching via Persistent Digital Identifier

A deterministic match using some form of a digital ID such as a login to an online account, cookie or device ID.

Trade-Offs

  • Less-scale as match rates to other digital ID’s will lower total number of users from the source file
  • Allows for greater insight into the consumer journey via cross-device graphs
  • Cross-device graphs enable digital targeting & activation
  • Sharing 1P data creates an opportunity for data leakage, data ownership rights need to be explicit
  • Enrichment is limited to known attributes from web-browsing, app usage, location data, etc.
  1. Look-A-Like Models (LAL) using Online/Offline Data

A probabilistic approach providing additional scale to find buyers that look like your target audience. Seed data, otherwise known as the truth-set is modeled. New users, fitting the profile of the truth-set are identified and appended.

Trade-Offs

  • LAL models can be quickly translated for use in digital campaigns
  • Requires common data between truth-set and larger data pool.
  • More data in common produces better models
  • Demographics are widely available across data-sets but are known to be poor predictors of behavior
  • Truth-sets often consist of loyal or high-volume buyers, which means non-buyers are excluded
  1. Social Affinity Audience Enrichment

A probabilistic approach relying on public brand engagements across social platforms.

Trade-Offs

  • Massive global scale with tens of thousands of brands eligible to be used for enrichment
  • Social affinity learning can be transferred to online & offline data
  • Uses same recommendation engine as Netflix and Amazon
  • No digital ID or sync required
  • Mapping process of taxonomy is a manual process that can take one to two weeks

The Affinity Answers approach to enrichment puts consumers first. It highlights details previously hidden from view, expanding your data’s potential. For example, Dunkin’ Donuts can leverage their fans interest in Blake Shelton and the Baby Bump app for insights and planning, but not if these insights remain hidden.

Contact us to uncover what’s hiding in your data.

Brand Ambassadors in the Programmatic Era

By | Blog

In this post we address how programmatic reduces the risk of picking the wrong brand ambassadors. Furthermore, audience data provide multiple ways for brand managers to make this important decision. Marketers can test a series of related third-party segments, or they can discover the insights and attributes right in their own data.

Read the full op-ed to discover how programmatic takes the guesswork out of a still very intuitive process.

AffinityAnswers Expands to The UK and Germany

By | Blog | No Comments

First Overseas Distribution of its Exclusive European-centric “Mutual Affinity” Social Media Audience Data

AUSTIN, TX (March 20, 2017) AffinityAnswers, which created the first platform for predictive branding – achieved through proprietary mutual affinity algorithms that measure active social engagement data across 60,000 brands and 400 million people worldwide – today announced it has expanded its offerings to the UK and Germany programmatic data markets.

AffinityAnswers analyses hundreds of millions of reciprocal, highly interactive social media activities (such as commenting, posting photos and videos, etc.) between brand audiences on social media, and then reports on which brand’s fans have the highest affinity for other brands, across all categories. By scoring any cookie- or device ID-based audience according to social engagement (aka “act-a-like” modeling) the company can predict which audiences will be receptive to any particular brand and are therefore more likely to respond favorably than the average consumer to their messaging and advertising. AffinityAnswers enables branding at scale through these high-performing “act-alike” segments available for programmatic activation across video and display, social, or TV advertising.

At launch, AffinityAnswers is offering about 150 pre-populated audience segments based on European data in major industry categories such as Apparel & Accessories, Automotive, Consumer Products, Electronics, Financial Services, Entertainment, Food & Beverages, Retail and Travel. In the UK and Germany this proprietary mutual affinity data will available through Google’s DoubleClick Bid Manager, MediaMath, and The Trade Desk, among other leading demand side platforms. Clients can get customized audience segments within three to six weeks.

“In our early testing, we helped an automotive dealership achieved 10x scale in targeted DMAs with minimal ad completion rate degradation; a new dairy-free yogurt brand targeted proxy affinity segments for a new product launch with a 70% increase in ad completion rates; and a gaming console conquest a competitor’s fans via an affinity segment to increase purchase intent by 9.1% as measured by Nielsen,” says Sree Nagarajan AffinityAnswers’ CEO. “Marketers in Europe have never had access to this kind of data that predicts how likely a consumer is to engage compared to the average consumer by uncovering relationships between brands that no one knew existed.”

The company plans to expand to other European nations later this year.

AffinityAnswers Used by brands, agencies and ad tech companies for activation, planning (media, creative, sponsorships), measurement, and strategic insights, AffinityAnswers measures across 60,000 brands and 400 million users worldwide the level of reciprocal, highly interactive social media activities to go beyond standard “look-alike” audiences to discover and activate higher performing “act-alike” segments for programmatic, social, or TV advertising. Its advanced machine learning technology is an unprecedented cross-channel recommendation engine that informs marketers about their audiences’ preference for thousands of TV shows, websites, apps, movies, music artists, and other consumer brands.

Founded in 2005 and headquartered in Austin TX, AffinityAnswers has offices in New York City, Chicago, Los Angeles and Bangalore.

Playstation conquesting lifts purchase intent

By | Case Study | No Comments

Using a branded AffinityAnswers’ segment to reach audiences of its competitor, a top gaming console was able to boost purchase intent during the holiday season.

With the holiday season of 2016 in full swing, a top gaming console wanted to do everything it could to steal market share from competitors.

The brand’s agency used an AffinityAnswers segment modeled after the social engagements of PlayStation. It was designed to reach branded audiences that were likely to engage with PlayStation on social and thus would be receptive to content or messaging from PlayStation. Since the gaming console category is very competitive, this segment was intended to pick up users that may be deciding which console to purchase.

After the campaign concluded, a brand study was conducted by Nielsen Vizu, a firm that specializes in measuring digital brand advertising effectiveness. A one-question survey was administered to participants, some of whom had been reached by using the segment and others who were not: how likely are you to purchase Brand X gaming console in the next 3 months?

The results were positive: those reached by the segment were 9.1% more likely than those who were not reached by the segment to state that they were likely to purchase the gaming console in the next three months. This was a big victory for the brand and for affinity-based targeting because it demonstrated that the advertising was effective, that the right audience was targeted and that affinity-based targeting is linked to the first step on the road to sales.

Contact us at hello@affinityanswers.com to find out how affinity-based audiences can enhance your Buyer-Driven Brand strategies.