Data

Weekly Digital Breakdown

Big Tech Could Be Required To Reveal Your Data 

With ongoing scrutiny of how big tech handles user’s data, specifically Google and Facebook, new legislation was introduced this week which could require companies to face more transparency than ever. The task? To reveal specifically what personal data is collected from users, how it’s used and what it’s worth as it pertains to advertising.

The proposed Designing Accounting Safeguards to Help Broaden Oversight And Regulations on Data (DASHBOARD) Act, would require companies with over 100 million monthly active users to file an annual report assigning value with user data collected. The act would also require full disclosure with third party partnerships who benefited from this information for financial gain. As part of the pending regulations, the SEC would be responsible for developing the methodology for calculating value to data obtained that all companies would have to adhere. 

While people around the globe access free services like Facebook and Google around the clock, most fail to realize that these companies cannot operate for free and use advertising to make a profit. While this may seem obvious, what they don’t understand is how these companies then leverage profile and behavioral data to help marketers narrow in on their target audience. The Dashboard Act also proposes users would receive their own report, potentially impacting online behavior and willingness to supply personal information.

As users are becoming increasingly aware of lack of privacy online, the bill would be an additional step to protect their personal information while increasing the bar for some of the largest data based advertising companies.

https://www.adweek.com/digital/new-united-states-legislation-would-require-internet-giants-to-disclose-the-value-of-user-data

Amazon Prime the Target of Competing Sales

With Amazon Prime Day quickly approaching, what started out as Amazon’s day to shine, has quickly become one of the most competitive shopping times of the year among e-tailers. Due to the overwhelming success of the annual event, over 250+ online retailers are expected to offer comparable sales July 15th and 16th in direct competition. According to a recently released study by RetailMeNot, Amazon Prime Day sales are the official kick-off for fall shopping, including purchases for back-to-school making it a critical time for retailers to capitalize on the excitement. The desire to get a piece of the action is well warranted based on last year’s sale beating out both Cyber Monday and Black Friday.

Target, in particular, has taken direct aim at the retail giant in its promotional push to encourage shopping during “Target Deal Days.” The event is being promoted for the same days as the Amazon Prime sale, in hopes of cashing in on the massive audience. The press release announcing the event goes so far as to address its sale has “no membership required” to shop and save on thousands of products, a not so subtle reference at Amazon’s membership requirement to receive the extended discounts. In addition, Target is offering the additional 5% discount offered to Target Redcard carriers along with multiple delivery and pick-up options, including same-day delivery.

There’s no doubt the playing field has changed for retailers in July. With over $4 billion dollars in revenue at stake based on Amazon’s sales in 2018, the competition is sure to heat up. In order to be part of the game, marketers need to be proactive, strategic and creative. The good news for shoppers, retailers are clamoring for your dollars which could result in record savings.

https://www.retaildive.com/news/target-aims-at-amazon-as-it-preps-for-another-prime-day-melee/557686/

Instagram Moving To A Shift In Focus

This week, Instagram publicly addressed the negative effects of the platform’s likes and how it hopes to implement changes to the experience. In what has been an ongoing conversation since April, Head of Instagram, Adam Mosseri, acknowledged the company is considering various changes including removing public access to the likes a post receives. The brand has not solidified a solution, but they are experimenting with ideas.The goal is to remove aspects that contribute to online bullying and narcissism, both of which can be detrimental to mental health and create a larger focus on community.

Instagram is also looking at other ways to make the site more focused on people connecting rather than competing. Another suggested idea is the implementation of warning notifications on comments deemed harmful or offensive. The alert would not restrict the comment from being sent, but would instead be an additional layer to remind users to be more mindful of what they are posting.

While nothing has officially been decided, the company is very aware of the impact the social platform has offline for users. Acknowledging the problem and working to create a solution, despite  the possible initial impact to the bottom line, could in the end, increase platform usage and engagement in a more positive and less competitive space.

https://www.cnet.com/news/instagram-boss-adam-mosseri-says-likes-might-go-private/














Getting Started With Marketing Personalization

To reach customers, a generic email, text, or Facebook ad won't cut it. Today's customers have high expectations. They expect personalized advertising that's relevant to their lives, and they are willing to help make that happen.

As many as 57 percent of consumers are willing to share personal data, as long as it results in personalized content and offers. At the same time, the majority of consumers (88 percent) aren't happy with the level of personalization they receive from brands they like, according to research presented by Econsultancy.

To help marketers better meet consumers' expectations, we'll explore what personalization is and why it's important, and provide a few tips to get started.

Personalization Defined

Personalization is more than just adding a customer's first name to an email subject line. Personalization is the act of knowing your customers and creating customized content and messages that resonate with each one. Customized content can take many forms. From sending a personalized promotion to customers based on their purchase history, to targeting a specific audience for a Facebook ad.

Why Personalization Is Important

Personalization helps brands attract and retain customers. By crafting messages and ads that are relevant to customers, you’ll draw more people in and keep the customers you have delighted with your efforts.

In time, you’ll build a relationship with your customers. It's similar to building a relationship with a friend. The closer you get and the more experiences you share, the more trust you develop.

As we've mentioned, customers want personalization. In fact, 58 percent of customers are willing to switch half of their spending to brands that excel at personalization, according to a recent report.

Tips to Achieve Personalized Marketing

To put your new personalization strategy into place, here are a few tips to get started:

●       Collect the Right Data

Get to know your customers. In today's modern age, that means collecting personal data. You'll likely need a tool or platform to collect, store, and utilize the data. Ideally, you'll get both demographic information (like name, age, and sex) and behavioral information that tracks things like past purchases and visit frequency.

●       Segment Audiences

Your customers are likely a diverse bunch. To pull off personalization on a large scale, you'll need to segment your customers, or break them into smaller, like-minded groups. Doing so gives you the power to create content for each niche.

●       Start Small

Create a small list of ways you can personalize your next marketing campaign. Don't try to do it all at once. For example, segment customers by location and send a promotion that's specific to a store in that area.

●       Test, Test, Test

As with any marketing campaign, you should test to see what's working and what's not. You can test many different personalization tactics. For instance, you can send an email that includes a customer's name and test it against a generic message that doesn't include the name.

Personalization is an important marketing and advertising tactic, but it takes some time and effort to perfect. You need to collect data and leverage it in a way that customers will respond to. Doing so will help you build a strong relationship with your customers.

4 Ways to Make Better Decisions With Marketing Data

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Effective digital marketing campaigns are built on data. Conversions, cost per click (CPC), traffic sources — with so many potential variables to analyze, it's vital to identify the data that is most important to your business. Data-driven marketing decisions can increase spending ROI and provide better, faster results. We've outlined four effective ways to make better decisions with your marketing data.

Use data to answer business questions. Where can we get the most value for our ad spending? How can we better reach our target demographic? By using marketing data to answer business questions first and provide insight second, marketers can speak the language of business with data-driven evidence. Individual statistics, such as the highest converting traffic channel or the lowest CPC ad campaign, work together to give insight into overall business goals.

Combine marketing and sales data for a complete consumer view. Remove the silos that separate marketing and sales data to form a clear view of the complete customer journey. Which traffic source produces the highest sales? Which ad campaign results in the lowest return rate? Data can tell the story of the customer's complete journey to product satisfaction, from the first ad view to a positive product review.

Use data to find new opportunities. Data can help you look outside your current campaigns for indications of new opportunities. Is there a surprising new source of traffic with high conversions? A new market may be revealing itself in your analytics data. After combining marketing and sales data, is there an ad campaign that produces high product return rates? Drill down on the advertising messages that resonate best with your customers. 

Make every marketing decision with data. Including data analysis as part of every marketing decision (rather than as an occasional addendum) ensures the process becomes a habit. Data-driven decisions can produce better, faster results than trial-and-error methods, and provide a mathematical basis for marketing campaign effectiveness.

A digital marketer has a mountain of analytics data at his or her fingertips. To use data efficiently and effectively, it's important to align your analysis with the goals of your business. From finding new business opportunities to increasing product satisfaction, marketing data has the potential to impact every facet of digital business.

Clean Marketing Data Is Critical — Here's Why

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Dirty data, or data filled with errors, leads to poor marketing decisions. It's a pervasive problem that affects nearly every business. After all, data is the cornerstone of the modern information age we live in — even more so in the new marketing landscape — which relies heavily on the complex information that's more readily available today than at any point in the past.

The volume of customer data collected every day is immense, which is why it's so common for companies to have, or plan to have, a large marketing database to corral all its customer data.

In a perfect world, collected data is used seamlessly to provide marketers with the insight needed to guide campaigns, make decisions, and target audiences for promoting specific services and products. Unfortunately, dirty data costs businesses billions of dollars every year and has far-reaching consequences.

To remain competitive, prioritizing data quality is essential. Adtaxi wants to spread the word with all the essential details you need to know, from what dirty data is to how to clean data for optimal results.

The Lowdown on Dirty Data

The Data Warehousing Institute estimates that businesses in the United States lost $611 billion in staff overhead, printing, and postage due to low quality customer data. The real cost goes far beyond that, as poor data quality frustrates prospects and alienates loyal customers while eroding a company's credibility.

So, what is it? The simplest definition of dirty data is a database record that contains errors. Those errors could come from inaccuracies that existed from the start or from changes over time. As TDWI points out, roughly 2 percent of the information in customer records become obsolete within 30 days as customers go through life changes including moving, marriage, divorce, and death. Data entry mistakes and errors that occur when source systems change is also problematic. 

Perils of Dirty Data

In truth, having great data is the foundation of any effective marketing campaign. It allows organizations to engage with their target audience and respond to shifts in dynamics quickly and effectively to get the most return on their investment. As mentioned, errors in the data making up your customer database can cost you. Some consequences of having bad data include:

●      Wasted printing costs

●      Inaccurate customer metrics

●      Tracking errors

●      Inaccurate marketing segmentation

●      Misleading customer records

●      Missed opportunities

●      Decreased revenue

 

Characteristics of Clean Data

There's more to clean data than simply making sure it's accurate. To judge your data as clean, it should meet five criteria:

●      It's valid: you can judge it as accurate or inaccurate

●      It's accurate, up-to-date, and as current as possible

●      It's complete: all the necessary fields contain all the necessary information

●      There's no duplicate information and there are no (or minimal) errors

●      All the data values are consistent — same time zone and same unit of measurement throughout the database.

 

How to Clean Your Data

Don't make the mistake of confusing data cleaning with data purging. You can have clean data without deleting old records, which can be useful for creating reactivation campaigns or generating scoring models. Instead, prioritize eliminating useless information with a multi-step cleansing process:

●      Complete a data audit to identify discrepancies

●      Set data cleaning workflow constraints as a team so the program knows what to look for and your team understands how to deal with anything that falls outside of those parameters

●      Execute the data cleaning workflow

●      Review the data to make sure it's correct and to manually correct anything as needed

 

To combat the changes that naturally occur, cleaning data should be an ongoing process for businesses and marketers alike. Collecting clean data from the start is a way to control data quality and reduce heavy data cleaning workflow.

 

The Effects of Facebook's Removal of Third-Party Data Targeting

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Say goodbye to data brokers and hello to a new way of reaching consumers. On March 28, 2018, Facebook announced it is banning third-party data targeting starting Sept. 30. The announcement sent a wave of apprehension through the marketing world. But there is some good news: Removing third-party data targeting creates more of a market correction, not a complete disruption. It might even give marketers better results in the long run.

What It Means

In 2013, Facebook launched its Partner Categories, which marked a milestone in the social media platform's partnership with large-scale data brokers such as BlueKai, Acxiom, and Datalogix. When it was created, Partner Categories was intended to provide advertisers with a way to connect in a meaningful manner with Facebook users, and get their brands in front of fresh, new eyes. The third-party data that has been collected has been used by numerous marketers and advertisers to target their audiences.

Marketers will now need to gain their data and information a different way, which is not necessarily a bad thing.

Self-Identified Data Performs Better

As helpful as third-party data might be, it's not the be-all and end-all of data targeting strategies. In fact, many companies leveraging self-identified data — or first-party data — experience better performance and unmatched power in connecting with their customers. First-party data is highly focused, and pulls information directly from customers using a company's website or apps. That's why many in the industry think first-party data is the way of the future in digital marketing.

Not sure first-party data can be effective? Consider this: A 2015 study conducted by EConsultancy and Signal revealed that out of 300 senior-level marketers, roughly 66 percent believe first-party data provides a better understanding of customers, which also leads to better overall performance. So even though losing Facebook's third-party data targeting might feel like a sucker punch for many marketers, it's an opportunity to shift strategies and boost results.

The Consumer Connection

What does it mean for users? Facebook's move to end third-party data targeting comes closely on the heels of the Cambridge Analytica scandal and a few weeks ahead of General Data Protection Regulation (GDPR), which becomes effective for countries in the European Union on May 25, 2018. This new regulation requires companies to get consumers' consent to collect data, giving consumers much more control over their personal information. That might be the largest impact on consumers.

So with its removal of third-party data, Facebook could be setting a new standard for the industry. This means marketers need to change with it, and continue using data collection strategies that best connect brands with potential customers.

Data Collection Isn’t The Enemy; It’s The Answer

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By: Andrew Ransom“Most ads I see are irrelevant to me.”

“Ads aren't very exciting.”

As brand and agency advertisers, we are constantly hearing from users and our clients about poor ad experiences. Ads are being served to irrelevant audiences, they aren’t captivating to users, or they provide a terrible experience by disrupting content. These are problems we work tirelessly to address, as our customers, and theirs, are best served by well targeted, engaging, and non-disruptive ads. And our biggest tool in addressing these issues is data collection; one of the least understood, and least trusted areas of advertising.

Before we get started, I want to address the elephant in the room. Proper, transparent, and ethical data collection, using third-party ad tags, must be the foundation for building a trusted ecosystem. This starts by eliminating the collection of personally identifiable information (PII). PII is essentially any data that could identify a specific individual to an advertiser. This includes names, addresses, etc. If we keep data collection anonymous, advertisers can still glean enormous insights without invading the privacy of those we are trying to serve.

How does user data help solve bad ads?

When a user browses the internet, visits websites, reads articles, or views ads, their browser is collecting things called cookies. These cookies collect information about the user’s behavior online; what sites they visit, what they’re shopping for, and more. This data is then used to bundle users anonymously into segments that share common behavioral, interest, or demographic traits. And those segments are how advertisers target users that may be interested in their products or services.

Thanks to this data, advertisers no longer have to serve ads to users solely through direct sales relationships or publisher-declared content categories; we are able to narrow down our reach to users who exhibit traits that make them more likely to be interested in our products. This increases relevance for users and advertisers alike, a true win-win for the digital ecosystem.

Tags also allow advertisers to cookie users who visit their website. By doing this, we can determine what categories of our products you’re looking for, if you added products to your cart and didn’t purchase, or if you actually completed a purchase. Knowing these things helps advertisers increase relevance another level. We can deliver ads that show you additional products in the category you browsed, we can send you a discount code for the product you added to your cart, and we can let you cool down after making a purchase so we don’t overwhelm you and create hostility toward our brand.

This non-invasive form of data collection is simple and protects the privacy of internet users. Because of these two things, even the smallest advertisers can now deliver a personalized ad experience for nearly every user. As more and more advertisers begin to adopt these practices, user experience will improve, advertising will become more effective, and we will create a more efficient digital economy for everyone.

How does data stop disruptive ads?

While collecting data on user behavior is an important part of improving digital advertising, there is another side to data collection that helps improve user experience across the web.

Tags placed within ads and on sites help DSPs, ad exchanges, and advertisers identify bad and disruptive ad inventory. When an impression is served we can tell where the ad is placed on the page, the probability that it was viewed by the user, if the ad was displayed in a pop-up window, etc. By identifying and eliminating these disruptive ads from the buy-side we accomplish a couple of things.

First, It allows us to stop buying disruptive ads. If they’re bad for the user, they’re bad for the advertiser, and we don’t want to spend money on inventory that will make users angry and potentially damage our brand. By eliminating this inventory from our campaigns, we reduce demand for them overall. As this continues to occur we will reach our second goal.

When demand for disruptive inventory reaches a certain point, it will become economically unsustainable for sites to continue to serve them. We will see DSPs and exchanges eliminate these sites from their inventory completely until disruptive ads are removed, and the industry will self-correct. We’ve already seen the beginning of this trend with Google’s latest announcement on ad blocking within its Chrome browser.

This type of data collection has a snowball effect. As it picks up steam, it rapidly helps improve the advertising inventory by signaling to advertisers which ad spaces are relevant, non-invasive, and provide a good user experience. As advertisers, when we see those signals we compete for those premium inventory spots, which pushes us to make more captivating and relevant ads as each impression becomes more valuable, and user experience is again increased.

What if we eliminated ad tracking?

As advertisers, we are sometimes asked why we track users at all. Why can’t we just let users view content in peace without following them around the web. The answer to that question is very simple and straightforward.

Advertising is how the internet gets paid for. It’s how companies, organizations, and individuals are rewarded for publishing captivating content on the web. Good content brings users, but users have an expectation online for content to be free. In order to maintain that relationship with users, content creators offer ad space to help offset the cost of content creation and to make a profit on their hard work. So, in essence, advertising will always be there as long as users expect content to be free.

If advertising is inevitable then we must make it useful to consumers. For nearly all its history advertisers could not track user behavior across the web. We were confined to purchasing blind impressions on groups of websites, purely because there were a large number of users there. Maybe we knew age and gender demographics of users, maybe we didn’t. But one thing was for sure, our ads wouldn’t be relevant to even a majority of those users.

So, for years, advertisers were forced to decide between boring and general ads that were made for everyone, or risk serving specific and irrelevant ads to millions of users. This was the equivalent of playing Dove commercials on Spike TV, or ESPN ads on Bravo. The ads were disruptive because users didn’t care about what was in them.

Now that we have the capability to deliver an ad experience tailored to the individual, where nearly every ad a user sees has some relevance to their life and desires, we have a responsibility to provide it to them. Providing a relevant experience increases user happiness, increases advertiser’s brand awareness, and increases profits. That’s why we track user data.

I’m still skeptical of being tracked.

As advertisers we have to respect that users will always be protective of their data, and they should be. And if we are going to collect their data, we have to set up safeguards to protect privacy. And that is what leaders in our industry are doing.

Data companies are providing data using double-blind methods, where the advertiser never sees the actual data, but is allowed to serve to audience segments based on a system of checks and balances. Data companies that provide better data get more business, and to continue to collect and provide good data they must protect user privacy. This adversarial system benefits user privacy while also providing advertisers with the tools to provide a unique experience.

Companies like Google, The Trade Desk, and others have also created coalitions to eliminate disruptive inventory on websites, allowing users to continue to view content without being interrupted. These coalitions are the watchdogs of advertising inventory. Their businesses benefit when ads are more effective, which happens when users are engaged.

These steps are the beginning of a movement in the advertising industry to restore trust between users and advertisers. This allows advertisers to truly understand what individual users want, and provide it to them. Proper and ethical data collection is not only a revolutionary movement in advertising, it’s a renaissance in the growing digital economy.