Nicolle Pangis - Xaxis https://www.xaxis.com The outcome media company Mon, 05 Dec 2016 21:26:31 +0000 en-US hourly 1 https://wordpress.org/?v=6.4.2 https://www.xaxis.com/wp-content/uploads/2021/06/cropped-xaxis-favicon-32x32.png Nicolle Pangis - Xaxis https://www.xaxis.com 32 32 How to Move Beyond Programmatic to Hone in on Consumers https://www.xaxis.com/how-to-move-beyond-programmatic-to-hone-in-on-consumers/ Mon, 05 Dec 2016 21:26:31 +0000 https://staging.lively-rate.flywheelsites.com/?p=30298 Originally featured in Ad Age, Get ready for the Age of Programmable Brands: How to Move Beyond Programmatic to Hone in on Consumers.
 
According to Get Ready for the Age of Programmable Brands, a November 2016 IDC white paper sponsored by Xaxis, 85% of U.S. media buyers use programmatic advertising. Yet brands don't have full confidence that they are reaching the right audiences with their messages in the right channels and frequency.
Programmatic media buying can be fragmented and siloed based on format or platform scale challenges when targeting a particular audience, which makes brand marketers feel challenged to cost-effectively find and target consumers in the most impactful ways. They need to tap into a new generation of tools powered by leveraging the most critical data from big data sets and machine-learning technologies that let them deliver personalized experiences to engage consumers in meaningful ways at every stage of the customer journey. Consumers then move effortlessly among platforms and devices.
So, too, must brands. As Karsten Weide, VP of Media & Entertainment at IDC, says in the new Xaxis-sponsored report, "You don't care about channels anymore, or whether your brand advertisement runs on display, mobile, desktop, connected TV or wherever else—it's who you want to talk to that matters."
Brands must become "programmable brands."
 

Connectivity: Just the First Step

First, programmable brands must connect to all the devices and technologies consumers use, then integrate multiple technology partners along the programmatic process into a seamless whole. They need the ability to see consumers as individuals in a unified—but anonymous—way as those people travel among different platforms and channels, a single view that reveals the messages the consumer has seen and where that consumer is in the marketing journey.
Rather than trying to guess where people might be, marketers need technologies that unify an individual's identity across devices—a foundational capability of programmable brand marketing. Programmable brands must also use data and analytics to find consumers at the right point in their customer life cycle with the right message. They must use the best data to deliver refined and honed experiences that the individual will value and accept, not avoid and block.
We are moving into a world where messages can be made substantially more relevant to a consumer than in the past by leveraging data and technology not previously available. Brands can then automatically and effectively deliver messages as the consumer moves from brand awareness, to interest, to consideration and purchase intent. With the proliferation of machine learning, a brand can even look back to the future in that we can model behaviors of audiences who performed a particular action and find consumers who look just like those consumers did 60, 30, 15 days ago and begin new consumer life cycles with machines.
Marketers can then quickly move spending and control sequencing across devices and platforms. Additionally, they can uncover overlooked ad inventory with high performance potential based on history while removing those ads that are not performing well down to a placement level.
 

The Programmable Vision

Programmatic is fast evolving beyond last-click performance metrics to incorporate the full range of brand-driven campaigns while doing so efficiently and cost-effectively.
The brands that lean into this fast-evolving digital economy—those that become programmable—will best succeed.
For further discussions, join us at CES in Building the Future of Advertising and Pioneering the Digital Retail Media Revolution.

]]> How to Make Data Smart & Machines Creative https://www.xaxis.com/how-to-make-data-smart-machines-creative/ Tue, 13 Sep 2016 19:39:46 +0000 https://staging.lively-rate.flywheelsites.com/?p=30345

Originally featured in Campaign as part of the road to DMEXCO series. 
 
In an already complex industry, we tend to overcomplicate. We all know the running joke that we put 3-letter acronyms on everything (and anything.) But when it comes to big data and smart data – and all the technology in between – we’re right to acknowledge the complexity. The truth is that the proper application of big data is extremely difficult and throwing more and more bodies at the problem is not the solution. At Xaxis, we believe that machine learning offers the missing piece of our industry data puzzle.
 
The Massive Effort of Data 
All companies have data – but they don’t necessarily use it in the most efficient way. Storing, extracting, and applying data in real-time is a massive effort, and if there’s a delay in time to market, an ad may no longer be applicable to a user.  We still have some way to go to ensure audience data is optimally leveraged in the creative and the way dynamic elements of the creative are leveraged on campaigns. But, a focus on efficiently using our data to boost brand allegiance and eliminate waste must become the standard of operation.
 
Shifting Towards Machine Intelligence
Creative and technology can talk to each other better than they did a couple of years ago, and they continue to come together even more closely. Part of the solution is machine intelligence. The majority of the digital ecosystem still manually manages small components of campaigns, including repetitive optimisation tasks that can and should be managed in real-time by machines.
At Xaxis we have our own machine learning technology called Co-Pilot, which helps us establish the best means of trading. In less than seven months, Co-Pilot has run over 5000 campaigns, and boosted client viewability KPIs by 30% in the US.  It also generated a 50% lift in trader efficiency. This frees up our operational teams to concentrate more on campaign strategy – where their talents truly lie.
Continued investment in data science feeds the possibility of machine learning becoming more prolific. Artificial Intelligence will never replace the capabilities of the operational teams and the data scientists – a balance between AI and human intelligence must be maintained. But, data science roles will become increasingly vital to organisations to inform machine learning.
This is not a simple evolution for our industry. It is one that will take time and will inherently change job functions, workflows, and how creatives are managed in digital. These three legs of the stool: the components of the creative; machine learning/artificial intelligence, and the smart application of big data will create the next generation of the digital ecosystem.  By nature, these types of changes will create an important, but complicated transition into the next evolution of our industry.

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