When Tom Ford released its first watch collection, the designer wanted to ensure that any of the models could be easily accessorized with its wide variety of strap options. Up until now, the choices have been limited to leather and fabric but this week Tom Ford is introducing a new metal bracelet …Reblogged 1 week ago from www.acquiremag.com
Sir Richard Branson has made it abundantly clear that Virgin Galactic will be getting people into space as soon as humanly possible. After opening Spaceport America in Las Cruces, New Mexico and then showing off…Reblogged 1 week ago from coolmaterial.com
The first quarter of the year is typically when ad-tech companies like to identify trends, measure consumer sentiment and behavior and gauge both advertiser and publisher appetite for different types of media, campaigns and ad units.
They’re looking for key insights that will guide decisions about strategy and tactics to employ throughout the year, sure, but it’s also a reality check; a way of asking: “Where are we now?”
Any survey that was conducted before lockdowns began in March and the entire world changed likely can’t be counted on: time spent with media (dramatic spike!), ad spend (consumer lockdown = budget lockdown).
But as much as we talk about “the new normal,” there are some areas that haven’t changed – and that I don’t see shifting anytime soon, no matter what happens.
Here’s what I’ve seen over the past year and continue to see today, from my embedded position in this industry.
Talk about a piece of the pie: Video accounts for 42% of all campaign spend on average. While mobile app publishers are allocating some of that to in-feed and social video, the vast majority goes to full-screen. Why? Full-screen is the most effective and garners the most excitement.
Half-page or display ads just can’t compete with full-screen when it comes to user engagement. Even when clients test in soft launches, working with any vendor, the result is the same – full-screen is better.
Consumers seem more comfortable with full-screen ads than even five years ago. We can thank connected TV (CTV) for that because it has conditioned us to sit through full-screen ads even in an on-demand, non-linear TV environment.
That behavior is true within mobile apps, too. When you’re playing a game and finish a level, you know a full-screen ad is coming. The difference, though, is that in many cases that ad is interactive, whereas most CTV ads are not.
Speaking of consumer behavior, it’s also clear right now that despite economic uncertainty, consumers are still willing to spend money on apps.
UA advertisers anticipated a decrease and had adjusted their budgets accordingly, but soon realized that wasn’t happening. We’ve seen the same level of spending over the last few months, and some games have even seen an increase.
Advertisers care how much each install costs them, and they want to pay the lowest CPI possible, even if that sometimes means struggling with hitting the right audience at scale.
From the ad network POV, that means I am constantly looking at the supply side and adjusting in order to meet outcomes.
While pricing is still the most important factor when evaluating performance of a network and ad campaign, other highly rated factors are quality of acquired users, volume, targeting capabilities, and level of service from the ad network.
And it is true that user quality, as measured by retention and lifetime value, is not to be forgotten. So I believe we will see more focus on engagement metrics in the future.
For ad networks to be able to optimize for performance metrics like retention, IAP and LTV, advertisers will need to be more open about their post-install data.
Sometimes they can be hesitant to share, but for ad networks to be successful and hit targets, they need that information. Getting the right user and ROAS data into our system helps us identify which supply sources are the strongest for that advertiser.
Compared to a few years ago, when UA teams were swelling, today the number of teams of 10 or more has actually gone down. From what I’ve seen, this is due to the consolidation of teams within organizations.
Rather than having an entire team that focuses on one title, they are combining groups to handle multiple titles at once, generally increasing efficiency.
And efficient they need to be: On average, UA teams localize for 7 languages and optimize campaigns five times per week. It’s important to note that optimizing that frequently can backfire; it’s harder to hit scale.
Campaigns ideally need to run for 14 days straight to gather the right performance data in order to know which supply will perform better to hit ROAS goals.
What is helpful to optimize right off the bat, however, is creative. Users are more willing to click to install when they see a new campaign, so I’d encourage switching those up earlier on.
These are the five trends – or rather, pillars, that are still standing strong – that will likely be unfazed by any additional shifts this year. These are rooted so deeply in our industry that I can’t imagine them going anywhere.
One 2020 milestone that will be interesting to witness is the impact of the July 1 deadline for CCPA. How will targeting parameters change as this privacy regulation takes effect and other states begin to focus more on privacy, too?
I’m very curious to see how the market reacts, as this was a long time coming – and now right around the corner.
Liz Waldeck-Pinckert serves as AdColony‘s Director of Client Partnerships for North America. Liz works with high profile mobile app publishers to help ideate and execute engaging and unique mobile marketing campaigns and advertising content to scale their business across North America. After years helping publishers monetize effectively and with exceptional user experiences, her unique insights are helping push results for mobile developers on both sides of the coin. Follow her on LinkedIn.
The post Good news for user acquisition: Consumers are still spending money on mobile apps in 2020 appeared first on ClickZ.Reblogged 1 week ago from www.clickz.com
As the red-hot arrival of Playstation 5 draws near, Sony is launching a new range of Bravia TVs that come “Playstation 5 Ready:” The XH90 offers 4K clarity at 120 fps and the ZH8 sharpens it up to 8K output. Both are driven by X1 processors which reproduce more colors than a conventional TV. They boast Sony’s super-bright Full Array LED technology & Acoustic Multi-Audio to deliver next-level surround. In Game Mode users can automatically play games on the PS5 console with low latency & control both devices from the wireless game controller. Due out for the holidays.Reblogged 1 week ago from www.werd.com
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The business marketing genius at the forefront of today’s entertainment marketing revolution helps corporate America get hip to today’s new consumer – the tan generation. When Fortune 500 companies need to reenergize or reinvent a lagging brand, they call Steve Stoute. In addition to marrying cultural icons with blue-chip marketers, Stoute has helped identify and activate a new generation of consumers. He traces how the “”tanning”” phenomenon raised a generation of black, Hispanic, white, and Asian consumers who have the same “”mental complexion”” – one based on shared experiences and values rather than the increasingly irrelevant demographic boxes that have been used to a fault by corporate America. But there is a language gap that must be bridged to engage the most powerful market force in the history of commerce. The Tanning of America provides the needed translation guide. Drawing from his company’s case studies, as well as from extensive interviews with leading figures in multiple fields, Stoute presents an insider’s view of how the transcendent power of popular culture is helping reinvigorate and revitalize the American dream.
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Marketing attribution is a way of measuring the value of the campaigns and channels that are reaching your potential customers.
By using the results of an attribution model, you can understand what touchpoints have the most influence on successful buyer journeys and make more informed decisions on how to optimize investment in future marketing resources.
But we all know that buyer journeys are rarely straightforward, and the paths to success can be long and winding.
With so many touchpoints to consider, it’s difficult to distinguish between the true high and low impact interactions, which can result in an inaccurate division of credit and a false representation of marketing performance.
This is why choosing the best attribution model for your business is so important.
In this post, we’ll discuss a bit of background on different attribution models, and ultimately, how to build a custom, data-driven attribution model to measure the performance of global campaigns.
All attribution models have their pros and cons, but one drawback the traditional models have in common is that they are rules-based. The user has to decide upfront how they want the credit for sales events to be divided between the touchpoints.
Traditional models include:
Luckily, there are more sophisticated data-driven approaches that are able to capture the intricacies of buyer journeys by modelling how touchpoints actually interact with buyers, and each other, to influence a desired sales outcome.
We also evaluated the Shapley model from cooperative game theory. This popular (Nobel prize-winning) model provided much more insight into channel performance than the traditional approaches, but it didn’t scale to handle the sheer volume of touchpoints in today’s digital world.
The Shapley model performed well on a relatively small number of channels, but most companies need to perform attribution for all campaigns, which can equate to hundreds of touchpoints along a buyer’s journey.
Markov’s probabilistic model represents buyer journeys as a graph, with the graph’s nodes being the touchpoints or “states”, and the graph’s connecting edges being the observed transitions between those states.
For example, a buyer watches a product Webinar (first state) then browses to LinkedIn (transition) where they click on an Ad impression for the same product (second state).
The key ingredient to the model is the transition probabilities (the likelihood of moving between states).
The number of times buyers have transitioned between two states is converted into a probability, and the complete graph can be used to measure the importance of each state and the most likely paths to success.
For example, in a sample of buyer journey data we observe that the Webinar touchpoint occurs 8 times, and buyers watched the webinar followed by clicking on the LinkedIn Ad only 3 times, so the transition probability between the two states is 3 / 8 = 0.375 (37.5%).
A probability is calculated for every transition to complete the graph.
Before we get to calculating campaign attribution, the Markov graph can tell us a couple of useful nuggets of information about our buyer journeys.
From the example above you can see that the path with the highest probability of success is “Start > Webinar > Campaign Z > Success” with a total probability of 42.5% (1.0 * 0.425 * 1.0).
The Markov graph can also tell us the overall success rate; that is, the likelihood of a successful buyer journey given the history of all buyer journeys. The success rate is a baseline for overall marketing performance and the needle for measuring the effectiveness of any changes.
The example Markov graph above has a success rate of 67.5%:
A Markov graph can be used to measure the importance of each campaign by calculating what is known as the Removal Effect.
A campaign’s effectiveness is determined by removing it from the graph and simulating buyer journeys to measure the change in success rate without it in place.
Using Removal Effect for marketing attribution is the final piece of the puzzle. To calculate each campaign’s attribution value we can use the following formula:
For example, say that during the first quarter of the fiscal year the total USD value of all successful buyer journeys is $1M.
The same buyer journeys are used to build a Markov model and it calculated the Removal Effect for our Ad campaign to be 0.7 (i.e. The buyer journey success rate dropped by 70% when the Ad campaign was removed from the Markov graph).
We know the Removal Effect values for every campaign observed in the input data, and for this example let’s say they sum to 2.8. By plugging the numbers into the formula we calculate the attribution value for our Ad campaign to be $250k.
The marketing attribution application above was developed by Cloudera’s Marketing and Data Centre of Excellence, but you can get started today on your own model.
By leveraging a data-driven attribution model you can eliminate the biases associated with traditional attribution mechanisms, and understand how various messages influence potential customers and the variances by geography and revenue type.
Once you have solid and trusted data behind attribution, you can be confident in using the results to inform and drive marketing mix strategy and investment decisions. And, you can rely on the numbers when you partner with sales teams to drive marketing strategies forward.
James Kinley is a Principal Data Scientist at Cloudera. He joined them from the UK defense industry where he specialized in cyber security.
The post Marketer’s guide to data-driven marketing attribution appeared first on ClickZ.Reblogged 1 week ago from www.clickz.com
Designed to go hard in the summer heat, Nike’s latest training shoe, the Metcon 6 is 16% more breathable than its predecessor, plus lighter, and it comes for the first time, in a flyEase variant. Developed with elite fitness athletes it features a Hyper Lift insert to support squats, snatches, & cleans, as well as a dual-density drop-in midsole for cushioning those box jumps & double-unders. Global release: August 31.Reblogged 1 week ago from www.werd.com
Bamford London’s GMT collection introduces a new colorway that should be familiar to many of you watch enthusiasts out there. The new Heritage and Heritage Edition Night Owl is the brand’s take on the popular “Pepsi” colorway with a red and blue 24-hour GMT bezel. It will also be joined by a new …Reblogged 1 week ago from www.acquiremag.com
Check out 1440–the fastest way to an impartial point-of-view. The team at 1440 scours over 100+ sources ranging from culture and science to sports and politics to create one email that gets you all caught…Reblogged 1 week ago from coolmaterial.com