Cookieless advertising: What you need to know as third-party data disappears

Author Jenni D'Alton

The words ‘cookieless advertising’ are enough for many in the digital marketing world to experience a feeling of hopeless abandonment. For years, marketers were afforded a huge amount of data such as user ID, user interests, or user habits, which they could leverage to support any of their strategic decisions. However, these glory days are soon to be over, because this data will be unavailable in the form of cookies on Google as of 2023. With Creative Automation, generating a vast amount of content is the key, and scaling content is the forward change for a cookieless future.

For over 20 years, cookies have offered businesses and advertisers a window into the world of consumers and their habits. Cookies, those miniscule pieces of data which track web visitors, are not in use in Firefox anymore and are set to become nonexistent on Google Chrome in 2023. Welcome to cookieless advertising. 

It will be a loss of tragic proportions in marketing terms as the ability to map a potential customer’s buying journey on the web provides rich insight for further advertising efforts. When cookies arrived on the scene in 1994, they mirrored the necessary operation of real-life shopkeepers taking mental note of the type of visitors and potential customers they had. Before cookies, shoppers were anonymous online, so it is not to overstate when we acknowledge that cookies revolutionized online shopping.

Cookies, while not a nutritious food choice, are the digital nourishment startups and emerging companies rely on for building their audience profiles and devising their marketing strategies. Consumers too were seeing less irrelevant ads, as a result.

What are cookies and why should you care?

> Cookies are files with small pieces of data which save your browsing information such as your location, username, or what is in your shopping cart.

> Cookies improve online consumer experiences as marketers and advertisers can use this information to more smartly and relevantly target their audiences.

> With cookies being sentenced to death officially by the end of 2023, marketing teams need to devise new ways to identify the interests and behaviors of their audiences, in order to deliver content that resonates.

Why are cookies disappearing?

The reason that cookies are being forced into retirement is largely a privacy matter, according to a Director of Engineering at Google Chrome. Users are demanding more transparency and choice around how their data is mined and exploited. The ePrivacy directive, which has become known as the “cookie law”, also was put in place to monitor the assurance of confidentiality and consent in electronic communications. This introduced the constant pop-ups you see asking you to accept, decline, or modify cookies from this website.

General Data Protection Regulation has also significantly influenced this move to cookie obsoletion. Inquiries have even been opened into whether the mechanism Google employs for building customer profiles in digital advertising is compliant with European privacy rules.   

But, a gray area will remain, just too gray of an area for marketers to bank on. Audiences are, as mentioned, requesting choice. Therefore, users can decide to “opt in” if they wish. However, audience sizes will reduce to an extent that the data is no longer scalable for any worthy media buying activity, likely amounting to low conversion rates.

Cookieless advertising: what are you losing out on?

In a cookieless world, targeted audience insights will be much less attainable. No longer will advertisers be able to easily tap into the proven interests and behaviors of those shoppers they want to know about. In a 2021 survey overseen by Boston Consulting Group, partnered with LinkedIn, concluded that 39% of marketers affirmed that data losses have already begun affecting their marketing performance and 56% expected this impact to grow. 

Dynamic display ads are a current example of how these live and historical user signals can be utilized, signals such as product affinities, geo-location, or Customer Relationship Management (CRM) data, to reach the right person. Dynamic display ads, a format in the Google Display network which changes elements of an ad based on who is viewing it, may be affected significantly as a result of the certain death of cookies. They are naturally cost-effective as they draw the attention of the people most likely to purchase your product, services, or solutions. However, in a cookieless world, Google’s options for rotating ads based on individual data is more limited.

This loss will be felt acutely by marketers who do not identify alternative strategies for ad targeting. But there is no reason to market completely blind.

What are your alternatives for targeting audiences?

1. First-party data

2. Gated content and progressive profiling

3. Federated Learning of Cohorts

4. Increase testing by scaling production with Creative Automation

What alternatives have you got?

Even though audie 

Data Vizualisation

 

Time and attention, as ever, are at a premium. Especially when we must work within the limitations of speed and resources while information and markets move and change ever more rapidly. AI and machine learning make it possible to gather, analyze, and interpret data into actionable insights at inhuman speed. But this data must be understood, translated, and shared. Quick, clear, and compelling data visualization allows you to present large amounts of complex information as a powerful story for any audience. 

Why does data visualization work so well and what are the best ways to visualize data and build your business?

 Let’s start with visualization. Most people are visual learners. We learn and communicate visually because compared to written language our brains have been processing visual information for much longer and have evolved to do that work more quickly and efficiently, much of it unconsciously. Research has been cited showing the brain to process images and graphic information up to 60,000 times faster than text. So maybe a picture is worth several thousand words.

And data, in itself, even when it’s arranged in expansive tables of numbers, is on the opposite end of the spectrum in terms of our ability to quickly process, compute, recognize patterns, and find meaning.

That’s unfortunate because among all the data is a wealth of valuable and important insight. However, the speed of data analytics tools and visualization software more than make up for our relatively slow thinking. It’s a perfect example of humans and machines teaming up with their complementary strengths to transform how we see and understand the world. The dynamic partnership of art and science in data visualization can spark explosive growth in creativity and revenue across your entire business.

Digital tools enable human analysts to study and interpret patterns and trends to gain actionable insights for making adjustments and developing initiatives. With AI and machine learning, we can distill galactic amounts of seemingly random and chaotic data that means almost nothing to any human staring at a sea of numbers in a table or spreadsheet. However, arranged as visual models, these insights tell a story or many possible versions of a story, and data-driven strategies are developed using the best, most relevant information.

Data, data, everywhere…

Data is the digital residue of the world in motion, of people living, working, and playing. It drives and is produced by business, science, technology, sports, and so many other human activities we don’t immediately associate with data, including art. 

Data is valuable because it tells billions of stories — stories within stories. Imagine Big Data as a massive human novel-in-progress, and we are all characters in it. If each word is one byte of data, then the world produces 2.5 quintillion words a day. That’s a word count equivalent to writing Tolstoy’s War and Peace about 1.7 trillion times a day, or 19,707,697 times per second. Let that sink in.

Everywhere, data flows and accumulates. But, of course, that’s not the end of it. 

You’ve got data. Now what? It’s time to analyze, interpret, and translate.

Now you need to find the stories within the data. You’ve got the raw material, the words and maybe some sentences and paragraphs, but none of that makes any cohesive sense yet. No one could pick a scene out of that mountain range of verbiage. 

Once you get that data, how do you make it work for you? While goals, audiences, and strategies vary by company, data visualization organizes information for quick and easy understanding across functions, industries, and even cultures.

In the same way that memes do so much work with an image and maybe a line or two of text, a graph can be worth a table of a million numbers.

Relationships between data sets become clear in seconds compared to hours of poring over the same information arranged in tables and spreadsheets, and still missing key trends, patterns, and connections.

Assemble the story before it’s too late

On January 28, 1986, the space shuttle Challenger exploded shortly after launch. During the investigation, it was discovered that colder temperatures compromised the integrity of the O-rings, which had become brittle and failed, leading to the explosion. Although engineers had gathered data and presented various data sets in several tables, key data sets of temperature and O-ring failure rates had not been shown in relation to each other. Experts had the data they needed but had not organized it visually, and missed the insight they needed when they needed it to make a decision that would have saved lives.

The power of data analytics and visual representation can give you real-time actionable insight to make data-driven decisions in the moment that impact every area of your business. Offer what your customers need and want. Build a stronger brand presence. Create better customer experiences. Fix problems early. And, depending on the context, even save lives.

Creative data visualization: Saving lives since 1854

Harmonize form and content to give your data life, and maybe even save lives

It’s not a revelation that representing data in a graph or chart or map can be a quick and effective way to understand and communicate information. Strong and compelling data made clear and understandable is approximately 43 percent more engaging and persuasive.

An early example of data visualization came from the work of John Snow, considered one of the founders of epidemiology, who tracked the cholera outbreak of 1854 in London by representing his data on a map. This helped him and others to see how the disease moved through the community. He figured out that the main point of transmission was a handle on a well pump, which was then removed, having an enormous impact on fighting the outbreak.

When interpreted and understood in a timely way, data visualization is a powerful guide for making informed decisions with confidence in their predictive power.

Flattening the curve with the help of data visualization

Examples of visual arrangements of data have been front and center since the beginning of the year.

Using three straight lines and two curves, the COVID “flatten the curve” graph has been successful in conveying two scenarios where, 1) we go about business as usual without practicing social distancing or any other measures to slow the spread of the coronavirus, or 2) we take measures to slow the spread of the virus, which is indicated by the shorter longer curve that stays below the horizontal line indicating the maximum number of patients the healthcare system can handle at once. The taller curve in scenario 1 rises above that line, meaning that the people represented by that area likely will not receive the care they need because the hospitals would not have the resources at that time.

That’s only a quick distillation of an explanation but is already far more cumbersome than the information quickly presented by a few lines and a couple of curves. Processing visual information 60,000 times faster than text sounds more believable. The data and the story are coded in the image of that graph, yet another image worth thousands of words as well as lives.

Another example includes heat maps showing areas hardest hit by COVID-19. The same data visualized differently as a bar or line graph shows the impact of various state or national efforts to control the spread of the coronavirus by comparing those who took varying stances on social distancing and shelter in place measures.

To show the possible speed and distance of spreading the coronavirus by ignoring social distancing measures, anonymized cell phone data tracking was visualized with a heat map to show how a small group of vacationers on the beach could impact the rest of the country by potentially carrying the virus back home with them.

Art and science come together

What form of visualization will bring the content of your data to life? That depends on what you’re trying to see in the data, what story you want to tell, who needs to see the story in your data, and other factors.

Watching data flows of all kinds is mesmerizing, satisfying, and incredibly informative all at the same time. An example of engaging and informative animated and interactive data visualization is Visual Capitalist. Take a look after you finish reading, though, because you’ll be there a while. Rabbit holes abound. 

Eventually, you’ll be ready to put your own data on display. Sometimes a simple pie chart or a graph will do the job. But if you’re looking to do something more creative with your data visualization to engage your audience, Tableau is an example of the current state of data visualization tools.

Gather and analyze data with purpose. Amassing huge quantities of information without rhyme or reason can still end up costing a lot of time and money and get you nowhere. 

Okay, so how can data visualization improve your business?

1. Locate processes and initiatives needing improvement or adjustment. Take the pulse of your people and your business to find sources of friction that can be smoothed out. Visualizing the right data gains faster buy-in and stronger alignment. Understanding the efficiency and effectiveness of workflows, hierarchies, and everyday business processes, as well as functions, such as marketing, production, sales, and service, can all be monitored by collecting data and then analyzing it in ways that reveal what otherwise goes unseen or unnoticed.

2. Understand your customers, partners, and other stakeholders. Take surveys. Monitor social media. Gather this important data with transparency and consent. The powerhouse team of AI, machine learning, Big Data, and the Internet of Things can collect, analyze, and help make sense of whatever amount of data you have and need. Knowing how stakeholders and customers are feeling, what they want, and how your efforts can be improved gives you the keys to respond with precision.

3. Predict marketing, sales, and other performance. One of the greatest values of Big Data, AI, and machine learning is the power to consult past and present trends and behaviors and then to predict what’s next, building an agile strategy based on the most probable models and scenarios.

4. Develop the most effective strategies for your situation. Data analysis enables your teams to see what’s working and what’s not, and, most importantly: why. Understanding the why can inform your problem solving, since data analysis is also finding problems as well as gaining insights to help solve those problems – whether it’s a quality issue, a situation or process causing churn, room to improve customer experience, getting ahead of shifting market trends, or pivoting operations to respond to major disruption. Seeing the data tell impossibly complex stories with a few visuals that replace the sea of data not only saves time and money getting to that point, but also in guiding your team to the right strategy.

5. Communicate and motivate using your data to tell a story. Customers, colleagues, and investors appreciate having complex information presented in a way that’s clear and easy to understand and use to make informed decisions. Conveying your knowledge, vision, and strategy often calls for strong data to back it up. Present your story with authority and confidence. Creativity inspires creativity.

6. Respond quickly, effectively, and creatively. Time is always in great demand and short supply. Speed remains essential to agility. Creativity is compelling. Gaining clear and current insights to inform swift, creative, and effective action is the advantage that data analytics and visualization grants companies who learn how to harness its cosmic scale of possibilities.

 By: Rena Gadimova

Position Preference in Adwords

                                                                                           

Position preference is a feature in Adwords that allows advertisers to request that their ads are shown in a specified position for any given keyword. It is important to note that with position preference turned on, Google cannot guarantee that your ad will be shown in the preferred position 100% of the time.

Optimizing Your Keyword Ranks With Position Preference
Conversion rates can vary drastically across keyword rankings. By using the position preference option, advertisers that have identified a preferred (higher converting or more efficient) rank can set a preferential ranking in Google.

For example: if your product or service does not tend to generate an immediate conversion response, you may find that the #1 & #2 positions generate a high number of click-throughs but a relatively low number of conversions. This will undoubtedly lead to an increase in CPA. In this instance the advertiser may consider setting a position preference of (3 - 5). These settings would send a request for an ad-ranking (3-5) assuming that the ad meets auction requirements for those positions.

The key to effectively utilizing position preference lies in the advertiser’s ability to cross-reference conversion data. This can be achieved by either setting up Adwords Conversion Tracker, Google Analytics or a third party analytics solution. In the early stages of testing, advertisers should monitor their performance as it pertains to their original ad rankings. This should act as a benchmark, followed by testing ads at different ranking ranges.

How to Enable Position Preference
1. Login to your Adwords account.
2. On the Campaign Summary page, select the box to the left of any campaigns you want to enable for position preference.
3. Click Edit Settings.
4. Find the Networks and bidding section.
5. Under Options, select the box next to 'Position preferences.'
6. Click Save Changes.

What Are The Position Preference Options?
There is a wide range of position preference options in Adwords.
- Higher than a given position (such as above 7)
- Lower than a given position (such as below 4)
- Within a range of positions (such as from 2 - 8)
- In a single exact position (such as position 2)

Does Position Preference Always Work?
The short answer is no, the top limit cannot be guaranteed, "...if there are 10 people with position preference turned on, and their top position is all 4, then if Google followed that ad serving plan, there would be 0 ads as no one wanted the top 3 spots. The bottom limit of position preference is a hard limit - the upper limit might not be."

While this example is an extreme case, it highlights the point that position preference allows advertisers to set a preferred position and that said position cannot be guaranteed.

7 Considerations for Tracking Social Media Success

7 Considerations for Tracking Social Media Success



With more and more marketers jumping onto the social media bandwagon, a lot of questions come up. Is it possible to track metrics and ROI? What are other companies doing? Why isn’t it working? Being prepared to answer questions like these can make a difference in how a company interacts with social media and if they can succeed.

How can we track social media?
Unfortunately, there is no one “most effective” social media tracking system. Marketers across the web are still working to figure out how to measure social media, how to attach ROI, and how to sell the benefits of participation on the social web to those that don’t “get it”.

Social media marketing isn’t like an email campaign where you can track the number of emails sent out, the number that were opened, the number of clicks, visits, leads and conversions all in one process. Much of what happens in the social media world happens behind a login and the old ways of tracking web visitor analytics just doesn’t work in that scenario.

Just like any kind of marketing, each company has their own set of objectives and reasons for reaching them via social media channels. That means different methods and approaches to the listening, monitoring and measuring of both social web and web marketing activities at large. The field of social media analytics is still very new. Here are 7 considerations as you evaluate what will work best in your social media tracking.

Quality over Quantity
This has been said again and again and lots of people still feel that the more followers/friends/subscribers/connections they have, the better. The reality is, quantity is not and end goal for lead or sales generation outcomes. What good is it to have 13,000 followers if 1/3 of them are spam accounts and 1/3 are auto followers who will never engage with you? Sure 13,000 looks good to those who can only focus on numbers, but what is the quality of those 13,000? Seth Godin mentioned at the MIMA Summit that all you need is an audience of about 1,000. But it needs to be the right 1,000 people.

Hearing vs. Listening
Have you stopped to think about who is actually paying attention in social networks? A person or a brand may have X number of followers or friends, but how many of them are actively listening at any given time? How many people do you ACTUALLY reach when you post a tweet, make a status update or blog post? Subscriber counts and reach are two different things. Think of it like a college professor talking to students: How many of them are paying attention during a lecture? With social media participation it’s the same thing; you need to realize that not everyone is always hearing what you have to say and factor in the difference between connections and actual reach.

Engage & Participate
Effective social media marketing is about is engaging and participating. If a marketer joins a social network and focuses on promoting themselves, product or company, they’ll get an entirely different set of outcomes than those they have goals for. Think about it. Social means to be conversational, friendly, helpful. When participating in social channels, talk to other members of the community, participate in the conversations and give people a reason to interact with you. Add a little romance before you ask to get engaged  

Social Media is About Being Where the Conversation Is.
Marketers need to stop and think about where their audiences are online and where relevant conversations are happening. That could be niche social networks, forums and blogs. Those niche areas may have fewer people, but will more than likely have more engagement value for relevant products or services being shared. To find those niche communities and conversations, use social media monitoring software. Free tools include Google Alerts or Social Mention. Low cost tools include Trackur and PostRank Analytics.

Assign Value to Get Value.
Whether it’s a tweet, retweet, a status update, comment, photo upload or story submission, if you want to find out how valuable it is you have to assign a value. It doesn’t matter how or what that value is, but setting up some sort of system will help determine what’s working and what’s not.

Define an Objective.
Before jumping into social networking, it’s essential to set an objective. Going in and participating with social network and media sharing sites just to participate may not bring the kind of results you’d like. A clear objective as part of a social media strategy should be set so you know what you are working towards. It will guide your messaging, behaviors, networking activity as well as the kind of content you seek and share.

Social Media is An Investment.
Social media success takes time. The seeds of relationships need to grow and you’ll need to invest what’s needed to make it work for whatever end goals that are set. Expecting results in a month or two isn’t realistic; it may take a year or more. It really depends on the Roadmap that guides your: Audience > Objectives > Strategy > Tactics > Tools > Measurement. Effective social media participation is about building a network and building trust. That doesn’t happen overnight. Be patient, do it right, and you’ll be rewarded in the long run.

What other considerations should be in this list? If you’ve undertaken new social media programs with your company, what were some of the measurement and analytics hurdles that you overcame?

PostRank Combines Google Analytics With Social Media Stats

Traditional web analytics tools like Google Analytics are a great for both small and large bloggers and publishers. However, traffic data can only tell you so much. As conversations surrounding blog posts start to take in place other places (Twitter, Facebook, FriendFeed, etc.) and people use tumble blogs like Tumblr and Posterous to quickly comment and share helpful information, tracking that data and its correlation to overall traffic numbers can become really, really helpful.For smaller publishers or bloggers, getting all of this information in one place can be difficult. Today, PostRank is publicly launching PostRank Analytics as a way to capture social engagement and traditional metrics all in one place.

When you sign-up for a PostRank Analytics account, you just need to enter in your blog address and connect your Google Analytics account. You can also enter in your Twitter username, so that your Twitter follower stats can be monitored in tandem with your web traffic.

What PostRank Analytics does is take the Google Analytics data and show you the pageviews, Twitter followers and “engagement score” for the day before. You can see how your figures stand up over time, by week, month or quarter.

But that’s just the beginning. The really cool part about PostRank Analytics comes when you evaluate individual blog entries. Not only can you see your total page views, unique visitors, bounce rate and average time on the post for each entry — you can also see how many people have tweeted about the post, how many comments it received, if there are any FriendFeed or Reddit reactions, was it re-posted on Tumblr, etc.
You can also see all of those reactions underneath the post. You get points for engagement and you can quickly determine which posts have high engagement scores and which don’t. What’s nice about this system is that you can compare the raw traffic metrics against the level of social engagement. So you might notice that something is a strong traffic performer, but has lower engagement details. Or maybe something is the opposite.

You can also see what types of posts tend to work best on what types of networks, and what impact that has on your traffic number or Twitter followers.

Earlier this week, I wrote about a new study that said 84% of social media programs don’t measure ROI. Although blogging is only one aspect of social media, it’s one of the easiest ways to measure feedback.

PostRank Analytics is a great add-on to Google’s own data. I would love to see the service monitor other types of social media accounts (like Facebook friends or fans) or plug into other analytics engines, but the data that PageRank Analytics can offer already is fantastic.

You can sign-up for a free 30-day test drive. Pricing starts at $9 a month after that.

How do you measure your blog and social metrics?