Google is expanding its tool for publishers to combat ad blocking.
"Funding Choices comes at a cost; publishers have to meet the Coalition for Better Ads’ Better Ads standards, which Google’s Chrome ad filter enforces and which some consider another way Google is dictating the rules of the web. Publishers also have to share the revenue with Google if they get readers to pay. Finally, few publishers are able to get people to pay for online access in the first place."
It should be noted that Google has (at least previously) paid two of the most popular ad blockers to have Google's ads whitelisted; effectively Google's revenue helps fund the development of ad blockers. Google then develops a tool for publishers to deal with adblocking...taking 10% (of monetised viewing) to do so.
While Google may be virtue signalling an intent to solve the ad blocking issue, it fully intends on capitalising on the revenue opportunity it represents.
This move (combined with their News Initiative to monetise new subs and GDPR requests to be 'controller') is aimed at making Google the gatekeeper to the content consumption experience for a large portion of the population.
Any other takes/perspectives?
The internet is predicated on the notion of it being free. But what if this predilection was found to be the root cause of most of our media and societal ails; filter bubbles, 'fake news', misinformation and the spread of conspiracy theories, privacy breaches et al.
Our technological and in some ways societal future depends on what happens next.
Jaron Lanier, a scientist, musician and writer is known for his work in virtual reality and his advocacy of humanism and sustainable economics in a digital context, and contends that when free digital systems and great tech entrepreneurs exploded there was a 'globally tragic, astoundingly ridiculous mistake, rather than a wave of evil where behaviour modification empires (we know them as social networks) sprouted and effectively 'broke' the internet'. He believes 'we simply just need to remake the decision'.
Lanier suggests, that born of this period (in the late 1990s) was a 'mythical power which produced two different passions; for making everything free and for the almost supernatural power of the tech entrepreneur. (But) How do you celebrate entrepreneurship when everything's free?' These two things are at odds with each other and this decision for predominantly 'free' has resulted in systems which modifies users' behaviour in the process of allowing them to seek information and communicate with others via the internet.
The only solution back then was the advertising model and just like users, the likes of Google and Facebook are hooked; unable to diversify from the proposition of cost centres to profit centres.
His most notable thought; "I don't think our species can survive unless we fix this. We cannot have a society in which if two people wish to communicate the only way that can happen is if it’s financed by a third person who wishes to manipulate them.”
Would/will users ever be able to be weaned from the 'free' model. Would we make a different decision if we knew back then? Would we being willing to remake the decision now?
A comprehensive and contextualised account can be read via New York Mag
Worth watching the TEDTalk in full.
Blockchain will affect the practice of marketing and the media industry in ways not yet entirely obvious but is it over-hyped?
No. It will be both inevitable and transformative.
Blockchain has been made possible with the convergence of scaled audiences, connectivity and computation power and provides a new data structure enabling what is known as crypto economic protocols. Blockchain is technology which decentralises the way we do business. Blockchain can create new network designs and supply chains and reduce the friction from many processes.
What this means for media and marketing is the way in which content is distributed and indeed the ownership, management and use of personal information and therefore the ability for marketers to reach consumers as they have done previously will be up-ended. Existing distribution models for both editorial and advertising content will be impacted by disintermediation and many AdTech and MarTech businesses will be under threat.
Plain and simple; if you're a media middle-man and you've read anything about Blockchain, you're likely to be a little nervous or amidst a period of heavy innovation.
We have reached a time right now where we're questioning how the tech giants ended up with too much power. Blockchain will be their likely usurper and from this, peer-to-peer for everything will become (the most likely) reality. How we never thought of this rather than allowing the rise of large networked empires will amuse future generations.
Blockchain is less about how the technology works itself and more about how it will be utilised and what the implications or impacts are.
As Jeremy Epstein from Never Stop Marketing discusses on the EchoJunction* podcast, with Blockchain we 'now have technology which allows for the transfer of items of value as opposed to simply information (like the internet delivered) without the need for third party intermediaries which add time and risk'. That is, we are seeing the distinction between the internet of 'Information' and the Internet of 'Value'.
Most significantly, it allows consensus about the state and ownership of assets at particular times and has strong security guarantees to ensure that 'history' cannot be altered by bad actors. This means this innovation enables or liberates all types of value (including content) as the owners and recipients are protected through verification.
According to Singtel's APAC Associate Director for Financial Services Industry Innovation, Cindy Nicholson, 2018 will be the breakthrough year for Blockchain and the technology will mature by 2025^.
This is what we will start to see:
The most significant change will be in the space where consumers themselves make money from their own data...but more on that later.
Waiting to see how it plays out is likely to see players 'left out' or 'left behind'. Education, preparedness and early experimentation (or partnerships) is key.
Update (April 10, 2018): Found this explainer on Blockchain which might be useful - A Beginner's Guide to Blockchain - Steve Sammartino
* The EchoJunction Podcast with Adam Fraser; Jeremy Epstein talks Blockchain
^ AdNews; In Depth - Can blockchain revolutionise how media is traded? and Blockchain Summit 2017
Here's another acronym to add to your marketing bible.
CDPs or "Customer Data Platforms's focus on 1st-party data and known identities and an ability to connect with common marketing systems for input and output. It facilitates data collection, unification around a persistent ID, flexible storage and easy access from outside. Caution: solving cross-device requires something that CDPs do not have (yet)."
A CDP could be visualised like this as suggested by Martin Kihn:
Gartner's, Martin Kihn's observations:
1. CDP is not a system of record – it's a system of innovation
2. Failures won't be caused by the tech – they'll be caused by you
3. You probably don't know how messy your data is now
4. You will overestimate your team’s technical skill
5. You want short-term results but use long-term evaluation metrics
The temptation will be to think the CDP replaces the DMP (Data Management Platform), but "The DMP negotiates...programmatic advertising, while the CDP – by definition – is grounded in individuals known by name, email, customer number or another personal ID." The DMP operates on massive audiences; the CDP, on a manageable number of individuals. They do different things but are complementary.
Here's a great summary from Martin Kihn in AdExchanger
At the same time we are being overwhelmed with the avalanche of streaming offerings, little is being said of the ability of Australia's internet to cope with the amount of data required for all the predicted streaming.
Akamai's State of the Internet Report is not comfortable reading. So why is Australia is becoming a digital backwater? With internet speeds ranked 44th in the world, studies cite the direction of the nbn as part of the problem (as reported by the ABC).
Reading Australia doesn't even have connection speeds above the average 10 Mbps 'high broadband' threshold is depressing, but to learn we are ranked behind New Zealand should surely spark the competitive nature in us to at least try and challenge our cross-Tasman rivals.
Operating in retail and online commerce, finance, telecoms, media, any subscription based or CRM gathering service you should be currently engaged in predictive analytics to ensure better understanding and retaining customers (or readers) and acquiring new ones more effectively.
Based on TDWI Research, the key reasons companies utilise predictive analytics are; to predict trends, understand customers, improve business performance, drive strategic decision-making, and predict behaviour. Predictive analytics is a must for retention, optimisation and acquisition strategies.
It's a bit of a (data) minefield getting your head around not just understanding and best practice predictive analytics (if you're like me and neither a data scientist or a mathematician) but also best understanding the appropriate product solutions for your personal and corporate use.
I'm loving the site Predictive Analytics Today. It's full of valuable advice and insights covering Predictive Analysis (of course), BI, Big Data and Text Analytics. There's news, reviews and tips plus plenty more to really geek out on. If you're just getting into predictive analysis, want to compare products or get the headlines of the offerings for confidence in decision making on supplier products and negotiations, there's a cheats guide to the best predictive analytics software. Incredibly useful and comprehensive.
Check out The Top 23 Predictive Analytics Software, as outlined by Predictive Analytics Today, which shows the usual suspects and arguably best providers in the likes of SAS, SAP and IBM with functions generally covering data mining, statistics, modelling,visualisation, econometrics, optimisation and forecasting but also summarises some lesser cited players like DSS (Data Science Studio) which enable correlation and significant variable data discovery and allows for testing of best fitting models.
There are also many free software solutions. Take a peek at the Top 12 Predictive Analytics Freeware Software. Everything from R and Orange to RapidMiner. Personally, I'm a little hooked on R at the moment. It's relatively straight forward and easy to self-teach. Certainly a great way to start building your confidence in PA software before investing in more intricate solutions.
Are there any on these lists you're using? Which ones so you rate?
How is your predictive analysis journey going?
Your comments are welcome and you are encouraged to express your views in a positive and productive manner in line with our Code of Conduct.