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Sentiment analysis is the practice of giving text a positive, negative, or neutral stance. It can use natural language processing (NLP) and machine learning (ML) technologies within the artificial intelligence (AI) sector to analyze and understand how customers are feeling.
AI is helping companies expand the adoption, effectiveness, and scale of sentiment analysis to adjust how they respond to customer opinion.
For instance, the NLP market alone is projected to grow from $20 billion in 2023 to over $127 billion in 2028.
See below for some of the top trends in the sentiment analysis market:
Human resources teams can benefit from developments in sentiment analysis. Creating a good employee experience is important for retaining and engaging employees. Employee burnout is common and knowing how employees are feeling can help keep productivity up within a company.
“HR teams can conduct sentiment analysis and deploy data-driven organization initiatives that focus on employee morale and things today’s workforce considers a priority, such as diversity and sustainability,” said Sameer Maskey, CEO, Fusemachines.
“HR teams also have the ability to leverage AI and data to understand the training needs across each department and create internal reskilling and upskilling opportunities.”
Michael Cohen, CPO at Achievers, says at CMSWire that it is critical for HR and other leadership to listen to their employees and respond.
“Artificial intelligence is one of the ways we can connect an entire employee population and understand what they need,” Cohen says.
Sentiment analysis can help HR improve a working environment, raise employee satisfaction, motivate employees to do their best work.
Read more: Top Natural Language Processing (NLP) Providers
Sentiment analysis can help companies understand how customers feel about a brand: positive, negative, or neutral.
“In addition to social media, brand discussion occurs on blogs, news websites, forums, and product evaluations,” said Gavin Johnson, managing director, EV Cable Shop. “Additionally, while it’s acceptable to monitor brand mentions (in terms of volume), it’s much more crucial to examine how they are referencing you.”
“Sentiment analysis can help you comprehend the subtleties of consumer opinions and provide useful context for quantitative data,: Johnson said. “You may track changes in brand opinion over time and identify any abrupt ones. To determine the effect of a PR crisis on your brand and analyze the effectiveness of your response, you can also monitor public opinion.”
Read more: 5 Ways Brands Underutilize Data Analytics
Customer engagement is essential in sales. Understanding what a consumer wants and doesn’t want can be efficient to changes within sale tactics.
“To engage prospects and make deals, effective salespeople each rely on their own beliefs, intuition, and experiences,” said Jake Cowans, founder, CompanyScouts. “Relying on these characteristics leaves a lot to chance and intuition. AI sentiment analysis can help to fix this and allow the salesperson to simplify their prospecting conversations by eliminating any uncertainty.”
Cowans also says the ability to know what a consumer is saying and feeling can help salespeople adjust their exact tone and language.
“Furthermore, SA tools can assist in locating keywords, competition mentions, pricing references, and a lot more details that might make the difference between a salesperson closing a purchase or not,” Cowans says.
Sentiment analysis and AI could be the answer to mental health treatment, according to TDWI With the ability to read emotions and learn responses, it is believed to be possible.
Some think that it might be dangerous to use AI in the mental health field. However, this trend is popping up more as a serious consideration.
Sentiment analysis has the potential to “pick up on nuanced language and tone that often gets lost in written communication,” said Adam Sypniewski, CTO, Inkhouse.
Sentiment analysis has the potential to be a tool in mental health care in a time where access to mental health care professionals is limited.
In terms of developing and implementing sentiment analysis for mental health care, Dr. Ronny Shalev, founder and CEO of Dyad Medical, believes, “The difficulties here are not only in terms of how much data we use to train the system, but how we approach cultural differences. … There will be differences in the way people express their emotions.”
“It is, however, achievable and will contribute a lot to the way humans will interact with an AI system, since emotions, even if artificial, gives us the sense of relatability.”
Consumers are the most important part of a business. With unhappy customers, a company can receive a bad reputation. Sentiment analysis can help with monitoring customer service, and experience.
For instance, using AI technology to analyze customer feedback and customer service exchanges, a company can adjust their service to improve customer satisfaction and loyalty.
“Now, with sentiment monitoring, AI analysis can automatically alert and bridge-in managers when needed as well as provide real-time analytics that streamline customer assistance,” said Ray Nelson, SVP of technical sales and services, ScanSource. “There are also companies who are using AI to analyze the call recordings to help coach call center agents after the call has been completed for future improvement.”
Sentiment analysis is “applicable to any customer-facing industry and is most widely used for marketing and sales purposes,” said Pavel Tantsiura, CEO, The App Solutions.
Sentiment analysis is making it easier for companies to pick up on customer reactions and emotions and reactions, giving them the option to learn and create a better experience for customers.
Read more: The Voice Recognition Market
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Sentiment analysis is a great way to understand the customers’ feelings toward a company and to see if they are associated with sales, investments, or agreements. Ensuring a reliable sentiment analysis depends on many factors, and one of its building blocks is the dataset used to train the models. However, finding the right dataset is easier said than done.
This article highlights the top sentiment analysis datasets to train your algorithms for more efficient and accurate sentiment analysis.
Although the quantity of the data is crucial, the quality or relevancy is also essential to have reliable results. For instance, if a retail company uses a dataset with financial jargon to train a customer sentiment analysis model, the algorithm may not provide reliable results as the words which the algorithm evaluates will be from a financial context.
So, having the right training dataset is crucial in evaluating the reviews, as you can develop new strategies with the insights you gather. Here we list the top eight sentiment analysis datasets to help you train your algorithm to obtain better results.1. Amazon Review Data
This dataset contains information regarding product information (e.g., color, category, size, and images) and more than 230 million customer reviews from 1996 to 2023. The reviews are labeled based on their positive, negative, and neutral emotional tone.2. Stanford Sentiment Treebank
Most sentiment analysis tools categorize the sentences by giving sentiment scores to each word without considering the sentence as a whole. Here, you can find almost 10,000 reviews on movies with sentiment scores ranging from 1 to 25. While 1 represents the most negative reviews and 25 corresponds to the most positive ones.Figure 1. An example of a movie review and the sentiment score of each aggregate 3. Financial Phrasebank
The financial phrase bank dataset contains almost 5000 English sentences from financial news, and all sentences are classified based on their emotional tones as either positive, negative, or neutral. All the data is annotated by researchers knowledgeable in the finance domain.Figure 2. Examples of the sentences from financial news and the corresponding sentiment label class
They can help your company with sentiment analysis services using a pre-determined training dataset to understand your customers better.4. Webis-CLS-10 Dataset
Webis cross-lingual sentiment dataset includes 800.000 Amazon product reviews in English, German, French, and Japanese. Its multilingual nature allows for reaching more audiences and conducting comprehensive analyses.5. CMU Multimodal Opinion Sentiment and Emotion Intensity
Not only do texts contain customers’ sentiments regarding services or products, but they can also be detected from videos or audio. CMU dataset includes multimodal data extracted from Youtube videos, such as the sentences and the voice tone used.Figure 3. The word cloud of the topics mentioned in the videos 6. Yelp Polarity Reviews
This open-source dataset includes more than 500,000 training samples consisting of consumer reviews, ratings, and recommendations. The polarity score of each sentence is determined, and the keywords requested can be extracted.7. WordStat Sentiment Dictionary
Wordstat Sentiment Dictionary classifies sentiments as negative or positive and combines three dictionaries: Harvard IV Dictionary, Regressive Imagery Dictionary, and Linguistic and Word Count Dictionary. The combination of different dictionaries allows for identifying synonyms and word patterns automatically.8. Sentiment Lexicons For 81 Languages
Although English is the most spoken language globally, it is also crucial to analyze the sentiment of other language speakers. This dataset includes 81 languages such as Chinese, Spanish, and German, so it offers a variety of data from different languages and represents the worldwide sentiment better.
Using a trained dataset to run your algorithm is essential in sentiment analysis. So, working with reliable sources matters.
For more in-depth knowledge on sentiment analysis, download our comprehensive whitepaper:
You can also check our data-driven list of sentiment analysis services.Further Reading
If you have further questions about sentiment analysis, do not hesitate to reach us:
Begüm is an Industry Analyst at AIMultiple. She holds a bachelor’s degree from Bogazici University and specializes in sentiment analysis, survey research, and content writing services.
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Sentiment analysis tools will help you evaluate the attitudes of your target consumers — attitudes that can make or break your brand’s reputation.
How do people feel about your brand — right now? This question may seem basic. But it can be critically important for marketers, as it should inform every aspect of your content and marketing strategies.
Social media sentiment analysis gives brands an opportunity to track online conversations about themselves and their competitors in real time. At the same time, they gain quantifiable insights about how positively or negatively they are viewed.
Social media sentiment analysis makes sure you know how every brand choice affects brand loyalty and customer perception.
It may sound complex. But there are plenty of tools to help you gather and analyze the social data you need to understand exactly where your brand stands.
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What is social media sentiment analysis?
Social media sentiment analysis is sometimes called “opinion mining.” That’s because it’s all about digging into the words and context of social posts to understand the opinions they reveal.
Measuring social sentiment is an important part of any social media monitoring plan.
How to run a social media sentiment analysis in 3 steps
In the section below, we get into some powerful tools you can use to help make social sentiment analysis faster, easier, and more accurate.
But if you’re not yet ready to invest in specialized social media sentiment analysis tools, you can get started with a bit of extra research.1. Monitor your mentions
The first step of social media sentiment analysis is to find the conversations people are having about your brand online. The challenge is that they won’t always tag you in those conversations.
Fortunately, you can set up Hootsuite streams to monitor social channels for all mentions of your brand, even when you’re not tagged. Here’s how to collect them all in one place.
In the Hootsuite dashboard, add a stream for each of your social accounts. This will track the mentions where people tag your accounts on social.
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You might want to organize all of your Mentions streams into a Social Mentions board to make them easier to view at a glance.
On some social media platforms, you can even track the posts where you’re not tagged:
For Instagram, you can monitor hashtags related to your products or brand name.
For Twitter, you can use hashtags or keywords.
Be sure to create streams for your brand name and your product or service names.
Again, a board can be a helpful way to organize all of these streams on one screen.
For more details on getting set up to track your mentions, check out our full post on social listening tools.2. Analyze the sentiment in your mentions
Next, you’ll look for terms that indicate sentiment within your mentions. Think about the kinds of positive or negative words people might use to talk about your brand. Examples might include:
Positive: love, amazing, great, best, perfect
Negative: bad, awful, terrible, worst, hate
There will likely be other terms specific to your product, brand, or industry. Make a list of positive and negative words and scan your mentions for posts that include these terms.
For Twitter, you can set Hootsuite up to do some of this work automatically. In the dashboard, create a search stream using your name plus 🙂 to indicate positive sentiment. Then create a search stream using your name plus 🙁 to indicate negative sentiment.
If you’re tracking sentiment manually, keep in mind that you need to watch out for the context. Is someone being sarcastic when they say they had “the best” customer experience with your brand?3. Calculate your social sentiment score
You can calculate your social sentiment score in a couple of ways:
Positive mentions as a percentage of total mentions
Positive mentions as a percentage of mentions that include sentiment (removing neutral mentions)
Which method you use doesn’t really matter, as long as you are consistent. That’s because the most important thing to watch for is change.
The second method will always result in a higher score.
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As we just said, Hootsuite is a powerful tool for collecting the data you need for sentiment analysis. These tools take things a step further by providing that analysis for you.
Hootsuite Insights powered by Brandwatch allows you to use detailed Boolean search strings to monitor social sentiment automatically. You’ll also get word clouds showing the most common words used to talk about your brand. Plus, charts that benchmark your social sentiment against your competitors.
In addition to positive and negative sentiment, Hootsuite Insights tracks specific emotions, like anger and joy, over time. This allows you to look for sudden changes, or ongoing trends. You can also filter sentiment by location or demographics, so you can see how sentiment varies across your audience. There’s also an AI analysis option to automatically identify the causes of significant changes in sentiment.
Alerts are another handy feature that allow you to be notified if there’s a sudden change in sentiment. Then you can get ahead of any issues before they get out of control.
Mentionlytics’s pitch is: “Discover everything that is being said about your brand, your competitors or any keyword.”
You can broaden the scope of your search to see what people are saying about your brand all over the internet. There’s a built-in sentiment analysis feature that works in multiple languages.
Digimind identifies and analyzes all the relevant conversations about your brand and competitors.
It pulls information from more than 850 million web sources, so you know you’re getting a comprehensive view of sentiment toward your brand.
You can also analyze mentions and apply filters to highly customize your sentiment analysis process.
Crowd Analyzer is an Arabic-language social listening and sentiment analysis tool. This is especially important for brands with an Arabic-speaking target audience. Other social sentiment tools do not generally have the capability to recognize sentiment in Arabic posts.
Source: Hootsuite App Directory
TalkWalker gathers information from more than 150 million sources. The tool then uses artificial intelligence to analyze sentiment, tone, emotions and much more.
Bonus: Free social media sentiment report template
Our social media sentiment report template provides the structure you need to create an impactful report to share with your team.
Bonus: Get a free social media sentiment report template to easily track audience sentiment over time.
3 ways to improve your brand sentiment on social media
The benefits of tracking social media sentiment are a little bit circular. For example, tracking social sentiment helps you better understand your audience, which in turn helps you improve social sentiment.
So, if you were paying attention to the benefits section above, these strategies might sound a little familiar…
Know your audience: When you know your audience well, you can craft messaging that connects with them. Basically, it boils down to this: Give your audience more of what they want and less of what they don’t.
Play to your strengths: Use social sentiment to understand what your audience thinks is great about your brand — and what they think is not so hot. While you work on improving the lagging areas, play up your strengths. Provide value while remaining true to your brand identity.
Why is social media sentiment analysis so important?
A simple tally of your social mentions only tells you how much people are talking about your brand online. But what are they saying? Social media sentiment analysis helps you answer this question.
After all, a high number of mentions might look great at first glance. But if it’s a storm of negative posts, it might not be so great after all.
In July, BMW’s social mentions spiked — but the engagement was not positive. Confusion ran rampant about a planned decision to sell subscription services for in-car functions. The Tweet that really set things off got nearly 30,000 retweets and 225,000 likes.
This is wild — BMW is now selling a monthly subscription service for heated seats in your car.
The car will come with all the necessary components, but payment is needed to remove a software block.
Welcome to microtransaction hell.
— Joe Pompliano (@JoePompliano) July 12, 2023
If the company had just been counting mentions, they could have thought they’d done something very right.
But the sentiment behind this increased activity was primarily negative. BMW was forced to clarify its subscription plans.
Let’s talk heated seats… ⤵️
— BMW USA (@BMWUSA) July 14, 2023
Here’s why your brand needs to track social sentiment.1. Understand your audience
Marketers do their best work when they understand their audience. That means you need to understand how your audience feels about your brand, your social posts, and your campaigns, not just how much they mention you.
For example, White Castle used social listening and sentiment analysis to discover that their customers have a positive association with the very specific experience of eating White Castle sliders while watching TV in bed.
With this knowledge in hand, White Castle featured a couple eating sliders in bed in their next campaign.
Source: White Castle ad via eMarketer Industry Voices
Ongoing social media sentiment analysis can also alert you quickly when customer preferences and desires change.2. Improve customer service
Monitoring sentiment provides two major benefits for customer service and support:
It can alert your teams to any new or emerging issues. You may even learn about issues with a particular product run or product. You can then prepare your team, or even create social content that addresses issues directly.
You can proactively reach out to people who may be having a challenging experience with your brand. A simple response or follow-up can often go a long way to resolve a customer issue before they even contact your team.
In this example, Adobe’s Twitter customer support team was able to resolve an issue and leave the customer happy even though they were not tagged.
Feel free to reach out whenever needed. Thanks. ^RS
— Adobe Care (@AdobeCare) September 26, 20233. Tweak brand messaging and product development
By following trends and investigating spikes in positive, negative, or neutral sentiment, you can learn what your audience really wants. This can give you a clearer idea of what kind of messaging you should post on each social network.
You may even gain insights that can impact your overall brand strategy and product development.
For example, Zoom monitored their social sentiment to uncover the biggest negative myths about their product. They then created a series of TikTok videos to bust those myths, improving customer confidence.
They also created a series of “Pro Tips” videos to answer the most commonly asked questions on social, thereby reducing the workload for the customer service team, while highlighting new features. Some of the ideas for new features even came from social listening and analysis.4. Understand where you stand in your niche
Brands cannot be all things to all people. Social sentiment can help you understand where you stand in your business niche. This, in turn, can help you reach the right audiences with the right messages at the right time.
For example, the production team at the media company Underknown launched a YouTube channel called “According to Science.” They told stories based on scientific research. But after 60 videos, the channel wasn’t growing.
After analyzing their data, the team realized that videos focused on survival got the most positive response. They tweaked their entire strategy and launched a new channel called “How to Survive.” The channel gained a million YouTube subscribers in only 18 months.
When they discovered their most positive responses came from Americans aged 18 to 34, they further adapted by creating short videos that live on TikTok and regularly get more than a million views.
Social media sentiment analysis can also help you understand in which areas of your business you really excel, and what you might need to improve.5. Spot brand crises early
You never want your brand to fall into a crisis. But if it happens, monitoring social sentiment can help you spot the problem early. You can implement your crisis response plan to minimize negative sentiment or avoid it entirely.
In the BMW example above, the car company took 48 hours to reply to the heated seats controversy on Twitter, and another day to get an official statement up on its website. By then, the issue had gained significant media coverage, making it harder for BMW to undo the damage. Had they responded within the day, they might have been able to correct the narrative before it got out of control.
Setting up automatic alerts for spikes in mentions and sentiment is an important early-warning system for brand crisis management.
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Non-profits need to use big data and mobile to present clear messages in 2023
2023 has seen charities gaining increased confidence to streamline, simplify and even surprise. With increasing demands from an ever increasingly digital savvy audience, standing still has not been an option.
The larger charities are capitalising on ever more sophisticated opportunities gained from insights and improved team working and systems. The best of the medium to small size charity websites are finding cost-effective ways to improve experience such as featuring user-generated content.
There are a host of encouraging trends in the sector, but these ones stand out to me due to their take up across the sector and positive impact are:
Clarity of message
It would seem that many charities have pared down their offering on key pages to focus on core content and calls to action. For many charities, this is most clearly illustrated on the Home Page where the key prompt is a fundraising ask. Web visitors who need more bespoke information rely increasingly on search and drop down navigation.
Move to mobile
The simplicity of messaging is at its most crucial when deployed on hand-held devices. With the marked increase in mobile and tablet usage, there is a strong focus on making websites serve up responsive design to enhance user experience and response. These distilled formats see bolder calls to action such as more prominent buttons.
This example of using context in Charity marketing from Chris Pook at Marie Curie shows how messages and offers can be tailored and tested by device and channel (Email vs SMS).
Really big data
Charities along with other key sectors such as financial services, were leading database marketing in the pre-digital age. With their established understanding of audiences, particularly donor trends, charities are joining up the learnings across the myriad of digital platforms. The importance of knowing who and why people are visiting websites and how it ties in with people’s broader behaviour has never been more important. The convergence and interpretation of these data sources will become increasingly more important as charities strive to maintain relevance and sustainability.
Best practice tip – Use XY profile mapping to summarise personas
Once the range of personas have been created, it can be useful to organise them in a graphical way to show the differences in behaviours and characteristics of the groups to help external audiences. The mobile sector example below shows how personas are mapped to show how they can be assessed according to their technical and social confidence.
Do just one thing for us
There is a move for digital to gain an increased share of voice from charity boards to staff at all levels. Over the last year, dedicated digital teams are increasingly collaborating, inspiring and informing. While I have highlighted singularity of purpose as a key trend, showing the full range of services and ways to support needs to be vibrantly illustrated. This is being achieved by strong content management and an incisive evaluation of web analytics.
Download Expert Member resource – Website practices for charities
This guide from charity digital marketing specialist Lucy Conlan will help you: Review your current approach comparing to other charity websites and align your website goals against objectives. It will also give you inspiration for improvements from examples of charity website best practices. .
Access the Website practices for charities
Every year brings with it new opportunities for digital success, and in this post, you will see my digital movers and shakers watch list for 2023.
The focus has been on the top search marketing and digital trends to keep a look out for so you can consider adding them into your marketing mix more effectively (or for the first time) as we move further into 2023.Social Media Slows but Will Continue to Grow
I feel like I am cheating slightly by adding this in, however, when looking at the dominant, unstoppable forces for 2023, I cannot omit social media. With new social media platforms entering the market and existing channels continuing to grow, this social media take over is far from over, although I expect the channel specific growth to slow somewhat.
Search Engine Journal’s Aki Libo-on wrote about this social media growth infographic that covers everything from active users and annual growth, through to user demographics and platform stats. Here’s a snippet from the infographic:
According to a recent report from Our Social Times:
Over a nine month period, the growth of Instagram far exceeded that of other social media platforms, including a growth spurt (between March and December 2014) where it surpassed the 300 million user mark and expanded its audience by approximately 50 percent
Facebook, surprisingly, had more video views in a single month that YouTube from desktops, however, the change in the Facebook video ‘auto play’ functionality likely had a direct impact on that
Snapchat is one of the fastest growing social media and messaging apps with six monthly growth in 2014 exceeding that of Facebook Messenger, Instagram, Pinterest, Vine, and many other alternativesLow-Cost Marketing Will Expand—It’s Not All About Emails
When you think of low-cost marketing the first item that often springs to mind is email marketing. By 2023, I would imagine that a vast majority of businesses have trialed incorporating emails for newsletters, company updates, industry changes, promotions, exciting news and more. By comparison, a fewer percentage will have expanded this low-cost marketing scope to incorporate items like text marketing (also known as SMS marketing and mobile marketing), but there is a growing trend.
According to UK SMS providers, Textlocal’s M-Commerce’ white paper, a company who I work with,:
Almost 4 million men and women in the UK are keen to hear from retailers by text at least once per month.
When you begin to broaden the types of low-cost marketing and expand the areas within the marketing mix that to employ, you will be surprised by the responses gained, even from the same distribution lists. One of the factors for this is that people digest communication differently, so acknowledging that in the diversity of approaches to your target audience will improve key performance metrics like open rates, response rates, and more.Digital Marketing Will Become Even More Integrated in 2023
When you have distinct search marketing and digital expertise collaboratively working, you will be able to mitigate most of the drawbacks of one marketing channel with the benefits of another. From initial objective setting and strategy creation, through to identification of key results, metrics for defining success, and ultimately actions completed – many more businesses will be investing in integrated search marketing as 2023 progresses.
Below you can see an example of a digital integrated working model:
To support effective integrated working, companies will become more creative in their delivery approaches including internal staff interaction, as well as the working relationships with external service providers, changing the historical outsourcing approach to increase the external team mentality.
Omni-channel marketing (really another means to describe multi-channel marketing) was a quickly growing buzzword in 2023 (starting its growth in late 2013), and the trend is set to continue globally in 2023, too. Here is an example of what this trend looks like (you can see the Google Trend here):Mobile Will be Included in Every Marketing Strategy
The growth of mobile search has been well documented and a recent study from Smart Insights tells us that this trend is going to remain active for some time to come. Mobile device targeting is not a new trend, but many businesses have not yet embraced it fully, or focused on the mobile opportunity enough to see it reach anywhere near its true ROI potential. A few key points from this recent study include the following.
Global mobile device users: Mobile users exceed desktop users on a global scale, this means that the opportunity to generate business value from effective mobile marketing has never been greater than it is right now. An increasing number of marketers are changing their approach to reflect this, and I see this continuing to build some momentum through 2023. There is some suggested plateauing of this, but I do not see 2023 being the time-frame in which this comes to fruition.
Internet access types: People are spending the majority of their daily internet viewing time using mobile devices, in fact, 51% of the total time spent in 2023 was with mobile phones and devices. When you consider the often intermittent mobile internet access (consider items like walking to and from locations, periods of working day downtime (breaks, etc.) and often quick internet access actions between tasks) this will shape many marketing approaches based on this and other behavioral identification too.Data: It’s Getting Bigger and it’s Real Time
When looking at digital industry trends and key movers and shakers influencing approaches to service delivery, you cannot overlook the role of big data and real-time data. Marketers have access to more information than at any other stage of human existence, and the challenge for successful digital marketing in 2023 and beyond is making meaning from all this data.
Data fuels everything from content creation and insights, through to reporting and strategy refinement. If you are making any digital decisions without data, you are likely overlooking a wealth of extra opportunity.
Here’s an example of a deep data platform in action. This is the Apollo Insights platform with information from the agency I work for, Vertical Leap. The screenshot demonstrates agile dashboard functionality, pulling in unique data sets for generating insights from information:What’s Next?
The digital industry is always moving at a fast pace, and perhaps it is the speed of change that is the main constant.
While I am confident in my predictions for 2023 digital trends to watch out for, I am aware that there is so much more that can be added to my list. On this point, I would love to hear what you think about my predictions for digital trend movers and shakers in 2023, as well as your own predictions.
Looking forward to hearing your thoughts and feedback.
In-post Photo #3: Image by Lee Wilson
CIOs should ensure that they know the top technology trends for 2023 for enterprise
Associations have gone through a dramatic transformation, sped up by the real factors of the most recent two years. Chief information officers are confronting refocused essential drives that are moving away from addressing the requests connected with the pandemic. With the digital transformations that have bloomed in endeavors beginning around 2023, CIOs have turned into a vital piece of plans to manage a developing client base that is fundamentally more technically knowledgeable. Now is the time for these CIOs to evaluate their organizational priorities and focus on trends that can help maximize the growth and impact of their businesses. The 2023 trends poised to shape automation this year and beyond will focus on modernizing the variations of workspaces—remote, hybrid, and in-office.Hybrid workplace enablement tools
The benefit of the hybrid work model is that employees can choose to work wherever and whenever they please, meaning they can schedule time for learning and improvement more easily than if they were fully remote or office workers. Learning, training, and development don’t just happen inside training courses. As the impact of COVID-19 persists and hybrid work continues, new and better tools to enable the mixed environment may emerge and CIOs should keep a close on these tools.The continuing data explosion
People and businesses are generating more data than ever before. Organizations presently gather gigantic measures of buyer information from an assortment of sources. However, much of this data is not being tapped into, as it is locked away in unprocessed documents. Numerous associations are arriving at an intersection and should decide how to use each of their information to illuminate direction or face the gamble of falling behind their rivals. Automation and intelligent document processing (IDP) solutions can transform inaccessible, unstructured data into structured, actionable data to give companies the ability to glean more data-driven insights.Widespread automation Smart space technology
This will be augmented with smart space technologies that help in building intelligent physical spaces, such as manufacturing plants, retail stores, and sports stadiums. According to reports, 82 percent of IT leaders agree that implementing smart building technologies that benefit sustainability, decarbonization, and energy savings have become a top priority.Collaborative data platforms
The ability to share data beyond organizational borders to create new insights is becoming increasingly important. The ability to create data ecosystems will be a top priority for enterprises in 2023. Secure, real-time cloud-based data exchanges, along with solution providers that enable collaboration based on data without the actual sharing of the granular data itself, are key enabling technologies here.Blockchain applications
The enterprise use cases for open-source distributed databases and ledger technology are becoming clearer. The four most important uses cases cited by IT leaders according to the survey will be secure machine-to-machine interaction in the Internet of Things, shipment tracing and contactless digital transactions, keeping health and medical records secure in the cloud, and securing connecting parties within a specified ecosystem.Generative AI
The world is abuzz with the promise of generative AI from natural-language generation models that can write computer code to algorithms that produce deepfakes. It’s not all hype. There are some meaty enterprise applications for generative AI, which is far more dynamic than the machine learning currently being used in most organizations.
Generative AI refers to the capability of artificial intelligence-enabled machines to use existing text, audio files, or images to create new content. In other words, it runs on algorithms that identify the underlying pattern of an input to generate similar plausible content.Next-generation EDR
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