Artificial intelligence has become essential to modern marketing. Companies are finding newer, more creatives ways to integrate AI into their marketing strategies. This goes for both brand and performance marketing.
AI can be useful in both online and offline marketing, but it tends to have greater efficacy in regards to online marketing strategies. Smart marketing executives are leveraging AI to boost the ROI of their online branding efforts.
One of the best ways to utilize AI in marketing is by taking advantage of contextual advertising. A number of artificial intelligence algorithms that have been instrumental in improving the performance of contextual advertising campaigns.
Contextual Targeting Advertising is becoming one of the most popular methods of serving ads online, due to these developments in AI technology. It is associated with positive results, and it helps to sidestep the privacy problems associated with third-party cookies. However, it is important to make sure that you avoid some of the common pitfalls of using AI in marketing.
AdMedia, a highly experienced company from Los Angeles, CA, explains how your company can build its image through AI-driven contextual targeting and contrasts the technique with behavioral targeting.
Explaining Contextual Targeting
Contextual targeting uses information from first-party cookies and the website where the ads will be placed to decide which ads should be displayed. Proprietary AI systems examine all aspects of the website where the ads will appear and all relevant data about the ad and the website to which it will click through. This form of advertising has several advantages, which will be explained below.
Three Major Advantages of Contextual Targeting
To understand why contextual targeting is superior to behavioral targeting when building your company’s image, it is necessary to be familiar with its advantages and how new AI algorithms help amplify them. AdMedia explains the positive aspects of contextual targeting, delving into how advertising can be a boon for companies of all kinds.
1. Contextual Targeting Drives Sales
Contextual targeting presents an advantage because it helps to drive sales. When your company’s ads are properly placed in areas where your targeted consumer segments are already browsing, you will have a better chance of capturing those visitors and possibly making a sale.
For example, if your website sells gourmet food, putting an ad on a recipe website or supermarket website will be productive. Customers may be looking for specific products to buy, or they may be interested in browsing just in case they see something they like. Either way, contextual targeting can help your company grab consumers’ attention.
AI technology can help immensely with maximizing sales volume from this marketing strategy. Machine learning algorithms are able to identify the variables that lead to the most sales, which helps increase the profitability of these campaigns.
2. Contextual Targeting Helps to Collect More Leads
Contextual targeting helps to collect leads because it appeals to customers. When customers click on your ad, they should be brought to a landing page where they can sign up for a special deal like free shipping or a percent-off coupon, or the opportunity to join an event. This can help you collect leads effortlessly.
You can also use contextual advertising in your email marketing. This means that your leads will be frequently contacted to keep your company at the top of their minds.
AI algorithms are great at helping drive more leads, because they can identify the types of visitors that are most likely to convert at any given time and make sure they are the ones that see the ads.
3. Contextual Targeting Builds Brand Awareness
Associating your business with another reputable firm is an excellent way to build brand awareness with AI technology. With Contextual Targeting Advertising, you are putting your ad where your best potential customers will see it. You may introduce your company to a new set of customers or reintroduce it to people who have visited your site in the past. For example, if you are running a car review website, you could advertise on a website that sells car and truck parts.
Contrasting Contextual Targeting with Behavioral Targeting
Behavioral targeting through AI technology became popular with the advent of third-party cookies. Advertisers could track purchase histories, browsing histories across all websites, and search engine histories, among many other criteria. Through this type of advertising, companies could track consumers’ every move online by placing cookies that traveled with them across websites. These cookies also captured shopping activity from various websites, aggregating them to create a personally identifiable dataset.
Behavioral targeting worked well for several years, but the upcoming removal of third-party cookies from three of the most popular web browsers (Safari, Chrome, and Firefox) will cause it to recede in popularity. The elimination of the third-party cookie is only a few years away, and websites that have relied on behavioral tracking will need to find a new strategy that uses AI.
Privacy advocates have spoken out against third-party cookies and behavioral targeting for several years. Bad actors can use this technology to hijack web browsing sessions. Ads served using behavioral targeting are also perceived as being creepy or intrusive in many cases. For example, many customers are annoyed when their Amazon search results appear on Google, Facebook, and Instagram.
Building Your Company’s Image
By taking part in consumer-friendly forms of AI-driven advertising like contextual targeting, your company will be associated with positive traits. Having a strong background in contextual targeting means that companies like AdMedia can reach the same sales and click-through targets as behavioral advertising firms without compromising users’ privacy and identity.
Personalizing Ads Without Intruding on User Privacy
Consumers appreciate properly personalized ads. They want to see advertising that is related to their search history and browsing history, within reason. According to AdLucent, 71 percent of all online consumers find targeted ads useful. They appreciate the convenience of having the right information served to them at the right time. This is where contextual advertising shines.
Personalization wouldn’t be possible without greater advances in AI technology. The good news is that AI has become more effective at identifying customer profiles and building personalized content for them.
Contextual advertising uses only first-party cookies and the website itself to serve ads. First-party cookies are easily accessible and are directly related to the site where the ads are being served. Within contextual advertising procedures, the information from the website where the ads are served is extracted through the proprietary process of Semantic Logic.
AI-Driven Contextual Advertising is the Future of Marketing
All companies that advertise online need to be aware of the coming elimination of the third-party cookie and its consequences for behavioral targeting through AI technology. Systems that use first-party cookies and contextual information are more likely to last well into the future when more privacy-focused website rules have been implemented.
Contextual Targeting Advertising is one of the best methods of reaching consumers today. Your company will find customers where they are already browsing, searching for products and services relevant to yours.
Knowing how contextual targeting can help your company is a must. Exploring all of the relevant aspects of contextual targeting helps choose a future advertising strategy.
Last year, one expert reported that Netflix used big data to grow to become a $100 billion company. This shouldn’t surprise anybody, because big data has been instrumental in their business model since the day the company was launched.
Netflix, by far, is one of the most reputed, loved, preferred, and biggest OTT Platforms and has also been around the longest. Even though the competition is at its peak and still increasing, Netflix’s user base didn’t shrink but expanded. Despite being a paid subscription service, it remains unbeaten. Of course, the web series, and movies on Netflix play a big role but there are more stories behind the Curtain.
As soon as a user opens Netflix, they find a list of recommendations and almost all of them match what they prefer watching at that particular time. This is not a coincidence that Netflix provides recommendations with such precision but there exists a complex process behind the accuracy.
It is obvious that Netflix does collect and process user data and uses them to recommend shows or movies to watch on Netflix. But what data does it actually process? Is it only watch history? Surprisingly, the answer is No. Watch history is only one part of the data collected and processed by them.
Netflix collects data on Searches, the time and date a show or a movie was watched, the device used, and whether the show or the movie was skipped, paused, or re-watched.
Looking at the myriad of content the Netflix library has, it will become haywire for a user to regularly search for a category or genre of the movies. This is where these collected data make sure that the user gets what they want to at that particular time and device.
2. Trends
On the top of the homepage, Netflix has a “Trending” row which allows their customers to figure out ‘What new they can go for’. Very evidently Netflix, not only processes individual data but also the crowd. They try to figure out what the crowd is preferring and make sure their individual audiences don’t miss out on them.
This complex intermixes of data collected on micro and macro levels also allows Netflix to decide which shows to drop which in turn helps them cut down costs on server rents and save & manage space on their server efficiently.
3. Original Content
Another new concept offered by Netflix as compared to the traditional streaming platforms is “The Originals”. As mentioned above Netflix keeps a close eye on what type of content is being slipped, paused, watched, and re-watched. This enables Netflix to get an overview, and an exact model of the type of shows they shall work on.
This is one of the key reasons why Netflix aces in the field of producing high-demand content. This collection of data and accurate algorithms enable Netflix to identify high-demand content.
This in turn enables the users to get the content they crave to watch and helps Netflix to gain more trust and reliability. And hence, maintain and increase their subscribers.
4. Marketing
You might have noticed that the thumbnails (or the posters) of the shows keep changing from time to time. And this is no coincidence that you end up clicking on one of the posters of the same show you chose to skip last time.
This is called the A/B Testing Method, used by a lot of businesses and can be further understood as a hit and trial method.
Netflix tests and tries different posters and as mentioned, they even collect data on every click we do, and hence they successfully finalize the poster that could be clicked by most of the users.
Conclusion
Netflix apart from being just a media services company is a business from a broader perspective. For any business to flourish and make an impact, the consumer base and cash flow are equally important. No need to mention that Netflix earns through its subscription price and hence, providing the best possible Value for Consumers’ money becomes more and more important.
Subscriptions being the core way for Netflix to make money, it becomes inevitable for them to create and provide valuable and efficient content and in this war of providing the best content its complex yet accurate algorithm seems to be the best supporter.
Analytics technology is incredibly important in almost every facet of business. Virtually every industry has found some ways to utilize analytics technology, but some are relying on it more than others.
The e-commerce sector is among those that has relied most heavily on analytics technology. Many e-commerce sites are discovering more innovative ways to apply data analytics.
One of the most important benefits of analytics in e-commerce is in the web design process. However, this entails many issues beyond the design itself. Analytics technology can help e-commerce entrepreneurs better understand their target demographics, conceptualize product launch offerings and much more.
Analytics Technology is Vital to Web Design in the E-commerce Sector
When you are trying to assess opportunities for a future resource and implement it successfully, you need to write down the features that you are looking for. When creating a business plan, you should think about the challenges you cannot accomplish without a good strategy and what strategy would work best to address them.
You will find that analytics will make these processes much easier. If you have any difficulties, please contact the hire e-commerce developer – Elogic. It is necessary to draw up a plan for the following purposes:
• set feasible tasks; it can be to genereate several hundred sales by the end of the year;
• analyze the prospects of the chosen niche;
• study competitors and understand why your offer is better;
• establish start-up capital, prescribe what you will spend it on;
• identify possible difficulties and how to solve them.
The good news is that highly advanced predictive analytics and other data analytics algorithms can assist with all of these aspects of the design process.
Selecting a segment with analytics
You need to choose the right niche for your future online store. Those who think that this is not an important task are mistaken. Working in an exciting niche that can generate income is better than working on a highly profitable one that involves a lot of boring activities.
Unfortunately, choosing the right niche can be a lot harder than you think. The good news is that analytics technology is very helpful here. You can use analytics tools like Google Trends and keyword research tools to gauge the general interest in a particular niche. You can also use data mining technology to learn more about the niche and find out if it will be a good fit.
There are specific criteria to understand when trying to choose a niche:
You can work on maximizing potential profit, but also going in a certain direction. This involves identifying an area of interest that will allow you to compete in times of crisis.There are prospects to expand. If you started selling women’s shoes, then in the future you can add shoes for for children and men.After the analysis, we learned what your advantages over competitors are. Perhaps you will provide expert advice when the client chooses a product, offers lower prices, and promotions.
If you have not decided what you will sell, you want to sell a product in demand, you can use the statistics of specialized services, research major players. Detailed market analytics will make this a lot easier.
Price segment for goods
The business will certainly not be able to cover the niche completely, so you need to decide which segment will be a priority. It may be cheap or expensive goods. The details differ in the following ways:
target audience, expensive things can be bought by entrepreneurs or travel lovers;for inexpensive goods, you can use messages in advertisements to attract the attention of potential customers to discounts;time to make a purchase decision, cheap ones, as a rule, acquire spontaneously, while expensive ones are looked at for a long time.
You can use data mining tools to aggregate pricing information of various products. After this is done, you can use analytics technology to assess your options and find out which products would be the best fit.
We are looking for reliable suppliers
Analytics technology can also help you scrutinize potential suppliers and decide which are best for your e-commerce site. This is a crucial step when launching an online store. Making the right choice involves determining:
quality of the assortment;choice;regularity of deliveries;the ability to make additional deliveries;preferential sales prices.
To find a supplier for an online store, you need to monitor search engines, specialized catalogs and services where joint purchases are made. If it is not possible to rent a warehouse, make purchases in bulk, you need an extensive assortment. You can use fulfillment or drop-shipping.
When you negotiate with suppliers, you need to ask:
whether they will be able to provide official documentation;minimum purchase lot;method of delivery of paid goods;who repairs or replaces under warranty;whether it provides photographs and descriptions of goods.
The fruitfulness of cooperation depends on this.
Drawing up a portrait of the target audience
Another benefit of analytics technology is that you can better identify your target audience. These are the people who may be interested in purchasing a product or receiving information. They should see promotional offers. If you own the data that the average customer in your online store is a middle-aged woman with higher education, lives in the capital and is preparing for a wedding, then you can:
make accurate targeting;prescribe effective messages;understand triggers to influence customers;decide on the promotion channels.Consider the type of target audience. There may be several of them:the main audience, which includes people making purchasing decisions;indirect – are related to the influence of the first type on the purchase;broad audience – people who are looking for the product that you offer;narrow audience – looking for a specific product model.
We create a brand and register a domain
The process of creating your brand is an investment that pays off for a long time, but with successful development will bring profit without effort in the future. This is the logo or name of the online store and the associations of customers with positive impressions.
Analytics technology can help in a number of ways. There are predictive analytics tools that can help you project the future value of a domain name and forecast sales potential based on the amount of search engine traffic that it could generate.
Analytics is Crucial to the Future of E-Commerce
The e-commerce sector is changing in response to data analytics technology. You need to consider the merits of investing in the right analytics solutions when designing a new website for your online store.
