Many digital marketers have embraced and incorporated artificial intelligence (AI) into their marketing efforts to streamline processes and optimize resources.
The Semrush 2024 AI Content Marketing Report for SMBs, gathered responses from over 2,600 businesses and found that 67% of them utilize AI for content marketing and SEO strategies.
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Leverage Local
If you aren’t using geo targeting with your social media delivery, you’re missing out. In a recent study by Neilsen, a global measurement and data analytics company, showed that buying local had the highest awareness among US consumers. BIA Advisory Services reported that geo-targeted ad sales are expected to reach $32.4 billion in 2021, up from $12.4 billion in 2016.
The 5-Day Weekend – Be Ready For it.
Timing is everything when trying to capture holiday shoppers. The 5-Day weekend is Thanksgiving Day through Cyber Monday and it accounted for 19.2% of total online retail revenue during last year’s holiday season. Make sure to budget marketing dollars for paid ads during this time period.
Make the Customer Experience Easy & Pleasant
Be sure to test your online purchasing experience. If its not fast and simple and mobile friendly, you’re going to lose sales. Its as simple as that.
Make the Experience Personal
A focus on personalization, both in print and online is more important than ever. According to a report from the Retail Industry Leaders Association (RILA) it found that 63% of surveyed consumers were interested in more personalized recommendations.
Another 64% of respondents were open to sharing personal data in exchange for retail benefits like loyalty points and coupons.
Your clients look to brand as a trusted advisor and are interested in brand-provided tips and suggestions.
The California Consumer Privacy Act (CCPA) will be enforced on January 1, 2020. We were nervous when the GDPR (General Data Protection Regulation) came into play, and that only governs the use of E.U. citizens’ data. The California law applies to personal data on any state resident, regardless of the location of the marketer. Many believe this is only the first of many states to follow.
Companies that are not compliant with CCPA are subject to hefty monetary penalties though a recent study of US Brands reflected that 56% of businesses surveyed don’t believe they will be compliant by the January 1 kick-off.
In the survey, many businesses sited the cost to become compliant as a major obstacle and equal to the price of a full-time employee. Some companies feel their business isn’t big enough to be subject to the law, or don’t think it applies to them.
To comply with CCPA, marketers must be able to respond to Californians’ requests about their personal data which include:
• Knowing what personal data is being collected
• Can request details on how their data is being processed
• Can access their personal data
• Can request to have their personal data deleted
• Know whether their personal data is sold or disclosed to third parties
• Decline or opt-out of the sale of their personal data
Many believe that the CCPA is complicated, and it is poorly written, leaving a lot of the verbiage open to interpretation.
The main goal of the law is to regulate the collection and sale of Personally Identifiable (PI) consumer data to third parties and service providers. You do not need to get paid for the data. If you disclose it to another party, it is considered a transaction. Using outside vendors to help manage your data is not a problem, because you are the controlling party.
Now, individuals can tell you to stop disclosing their data to others; and you must comply. One cannot deny goods or services to anyone because of their data opt-out and that is making for a slippery slope. In order to know you are not supposed to have data on an individual, you must have that individual in your database. And since it is likely you must have data on an individual in order to do business with him or her, how do you conduct business with data exceptions? One writer compared it to The Eagles Hotel California tune, “you can check out any time you like, but you can never leave.”
Starting January 1, California’s Consumer Privacy Act (CCPA), will require all California for-profit businesses to disclose to consumers upon request the specifics of the personal information collected and its sources. Consumers can also require companies to delete personal information, refrain from selling it, and pursue legal action for failure to comply.
As the start date for the law draws near, giants like Google, Amazon, and Facebook, are working to help push through amendments that will make the law easier on businesses.
California is the first government in the US to regulate how businesses retain and use electronic consumer data. The legislation is the first response to the European Union’s GDPR, enacted last year. The General Data Protection Regulation allows the EU the power to fine companies that violate its consumer privacy protections. Google was slapped with a $57 million fine for failing to disclose data collection tactics to consumers, and Facebook is under several investigations from the GDPR governing body.
Personal information protected by CCPA include:
Fines for non-compliance range from $2,500 (if unintentional) or $7,500 per violation (if intentional) for companies that fail to cure alleged violations within 30 days.
As efforts to pass federal privacy legislation in Congress have languished, states have stepped up their pace. According to the National Law Review, five other states — Hawaii, Maryland, Massachusetts, Mississippi, and New Mexico — have introduced CCPA-like privacy bills as of March 2019. Another three states — New York, North Dakota and Washington — have put forth consumer privacy bills to protect personal data.
A federal bill introduced in the Senate in December, The Data Act of 2018, remains in committee. As proposed, among other protections, the legislation would prevent “online service providers” from using individual identifying data in any way that would benefit the online service provider to the detriment of an end user.
Email campaigns work. We have a client that offers summer camps as part of their service offering. In the spring, they paid for a booth at a local event that promoted family friendly products and services. We printed fliers promoting summer camps and different types of lessons ranging in price from $200 up to $400.
During the event, they had a drawing for a free, 1-hour lesson and collected names, email addresses and phone numbers from attendees. By the end of the show, they had collected 99 prospect names.
The following day, we input the information into their email database and generated 2 emails. The first email was announcing the winner of the drawing with instructions on how to collect their prize.
The second email was to the 98 individuals that did not win. The email offered a 25% discount on a summer camp, as a way of saying thank you for dropping by their booth.
Both emails were sent within 24-hours after the show. The results are typical and confirm the benefits of using email blasts.
The promotion email had 16 bounces (16%). That is very high, but it is normal for a show. People had to hand-write their information and often it is difficult to decipher handwritten information. 82 emails were successfully delivered.
Three people purchased summer camps directly from the email campaign generating $1,200 in sales. In addition, one person signed up for six-months of private lessons ($1,800) and another signed up for group lessons for 2 months ($400) bringing the total sales from the email to $3,400.
Quality targets, timing, eye catching graphics, compelling content, and a call to action make for extremely successful email campaigns. If you aren’t incorporating email in your marketing strategy, you’re missing out on sales.
In the 1980’s, the MRI (magnetic resonance imaging) made the human brain visible in ways never seen before. Doctors were able to see brain structure and the soft brain tissue of a living object. This type of detail was only seen previously during autopsies.
During the 90’s, the fMRI (functional MRI) came into its own. The fMRI detects blood flow revealing brain activity which makes it possible to identify which parts of the brain react to scent, visual recognition or even sound.
The fMRI is in transition once again. Though still in development, the fMRI will soon allow scientists to track the condition of our mind with more precision. As researchers analyze the vast amount of data generated by brain scans coupled with the latest computational techniques including Artificial Intelligence and Machine Learning, scientists are beginning to resolve how our physical brains form our mind.
The research may have a significant impact on marketing, police work and computer interfacing and may even allow the preservation of memories even after an individual has passed.
Some mental functions activate several parts of the brain at the same time. The fMRI can detect that activation and machine learning deciphers patterns into specific descriptions that include what a subject is thinking or doing. In an article published in the WSJ by Jerry Kapalan, Kaplan said’ “It’s like going from identifying individual letters to reading words and sentences.” That’s big!
Studies show that people’s brains organize and process the same information in similar ways. Collaborators in a 2011 study were able to correctly identify which of eight mental tasks a subject was performing 80% of the time, based solely on looking at their brain scans.
The evolution of brain reading continues with Functional Near-Infrared Spectroscopy (fNIRS). This emerging functional neuroimaging technology offers a relatively non-invasive, safe, and low-cost method of monitoring brain activity. fNIRS is the measurement of near infrared (NIR) light that takes advantage of the optical window in which skin, tissue, and bone are mostly transparent while blood flow is a stronger absorber of light allowing for a more in depth reading of brain functionality.
The ability to decipher this type of technology raises questions about the privacy of our thoughts. It may lead to a world where our mind is subject to a search warrant or become a matter of public record leaving the ever pressing question of who should have access to those thoughts, and how they should be used.
Global spending on Artificial Intelligence (AI) is expected to reach $35.8 billion this year. That’s up 44% from last year. It’s expected to double to over $79.2 billion by 2022.
Below are some terms that will help you to better understand this exploding and learned technology.
Natural Language Processing (NLP) –A subfield of computer science, information engineering, and AI focused on interactions between computers and human language. When text or speech is input and it can be read or extract meaning.
Artificial Intelligence (AI)- Sometimes called machine intelligence, AI is intelligence demonstrated by machines. These machines mimic “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”.
Deep Learning -Sometimes referred to as deep structured learning or hierarchical learning, it is part of a broader family of machine learning methods based on artificial neural networks.
This powerful statistical technique is used for classifying patterns using large data sets and ANNs (Artificial Neural Networks). Deep learning neural networks have been applied to fields including natural language processing, social network filtering, drug design, medical image analysis, and game programs. They have produced results comparable to and in some cases superior to human experts.
Machine learning (ML) -The scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. Machine learning algorithms build a mathematical model based on sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to perform the task. Machine learning is closely related to computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a field of study within machine learning, and focuses on exploratory data analysis through unsupervised learning. In its application across business problems, machine learning is also referred to as predictive analytics.
Artificial Intelligence (AI) is able to measure tone, tempo and other voice characteristics. Some systems compare those sounds to stored speech pattern libraries that define a plethora of human emotions to determine an individual’s emotional, mental or even physical health.
When this sound technology is used in conjunction with computer vision, the science that allows computers to gain a high-level understanding from digital images or videos, the applications become even more powerful. For example, imagine a vehicle that is able to hear a driver yawning and see the driving dozing off.
Research firm Gartner Inc predicts that within three years, 10% of personal devices will have emotion AI capabilities that include wearables (similar to a Fit Bit) that is able to monitor an individual’s mental health or video games that adapt to the players mood.