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Thought leadership, insights, and stories from Brightaira


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Are you struggling to choose the best marketing strategy or measure the effectiveness and adequacy of your marketing campaign? You are not alone I’m too.

I’m no expert in marketing strategies so to set this straight before you go ahead and read the entire article, but I’m an expert in digital transformation and building intelligent systems that can advance your marketing strategy.


Today, most organizations follow a conventional and traditional approach to develop their marketing strategies. It involves a great deal of effort and requires good study of the market and alignment with the cooperate strategy. However, I would argue that these strategies are predominantly based on past experience and little to do with “your data”. It is rare to see organizations employ advanced analytics to build their strategies. Mostly, due to technical complexities or inability to harvest the data.


Data-Driven Organization

You must have seen this title before. Numerous organizations like to put this title in their strategies to indicate the organization puts data first. Although, this is a great direction to take, however, few organizations do manage to perfectly implement. Only those who really understand how to put “Data-First” manage to succeed in building a data-driven organization.


Building a “Data-Driven Organization” is a rather extremely challenging task. It would take the entire organization to achieve it. Many processes need to be redesigned, rules need to be rewritten and business logic needs to be rethought. Equally, the IT infrastructure needs to be ready to help achieve that from building systems to storing and manipulating data.


Data and Marketing

No matter how good and robust your strategy is, it will be extremely fragile if not based on facts and data. Strategy after all is a process; a thoughtful process; you need to collect data about your organization, products, customers, partners in order to tailor the strategy to work best for you.


The data is available in two places. One within your organization’s systems and the other outside your perimeters. The latter is mostly found in open data. Nowadays, social media and global news on the internet represent a big portion of that data. That is why organizations these days use social media monitoring tools to monitor and observe what people are exchanging about them and their brands.


Social Media and Marketing

Companies today are in a race to attract more customers and promote their products to consumers online and most specifically over social media platforms. It has become a practice to analyze what people say over social media platforms to measure the performance of the marketing and communication department. It’s really such a powerful tool and we have seen the impact they present on the social, economic and political life we have today.


Artificial Intelligence and Marketing

Artificial Intelligence was introduced to solve the inability to process a massive amount of data and spot important things like when people are happy or angry about a service or a product we have. Many tools today offer basic to advanced Natural Language Processing to read the unstructured data make sense of it and present insight that could help organizations improve their services.

AI can be used in various marketing scenarios and I will give a shortlist of potential scenarios where AI can be of help

  • Personalized Recommendations: AI can be used to help deliver personalized content and therefore improve the chance customer click or choose a product or service. With proper data planning, you can collect information about your customer preferences (with consent) and display the relevant products and services.

  • Customer Care: Customer care is a big umbrella that covers interacting with customers, receives feedback and process customers’ requests. AI can be used in various touchpoints within the customer journey.

  • Conversational Agents (Basic & Advanced Chatbots): Chatbots and conversational agents are becoming more and more widely accepted due to the high adoption by many organizations.

  • Content & Website Design: Today, there exist many tools that help in content generation and website designs recommendations. Organizations can easily leverage these tools to easily create and publish compelling contents.

  • Advertisement Bidding: AI is used in all advertisement platforms and organizations can use these available features. For example, you can let google ads decide what best work for you! And without the need to understand how bidding strategies work.

  • Understand Buyer Persona: Understand the buyer persona is key. You can use AI to determine the “intent” of the prospect request and then deliver the request to the right team.

  • Audience Targeting: You can use analytics and advanced analytics to determine the right target audience. You can also use AI tools to screen the public data and generate insights that can help you define your target audience.

  • Topic & Title Generations: Perhaps this is one of the most challenging tasks in AI and today we see quite good advancements in this field. You can generate titles and topics that attract more customers.

  • Customer Churns: Identifying the customers churn is important. You can direct certain marketing campaigns or offer discounts for customers likely to churn.

  • Lead Scoring and Health: You can use AI to assign a scoring for each lead to help sellers quality the lead. This helps optimize the quality of leads and the sales team’s ability to utilize the marketing efforts.

Marketing Recommendation Platform

Realizing the importance of digital marketing and the current gab in finding the right tools to help markers achieve better decisions. We at Brightaira decided to build a platform that helps people working in marketing and companies make decisions with regard to the services and products they provide.

Brightaira, is an advanced artificial intelligence global media platform that assists organizations in making decisions in the area of Marketing and Customer Success. Brightaira collects Millions of NEWS and SOCIAL MEDIA feeds, analyzes them and provides organizations with the insights and decision choices to help optimize customer experience and improve business outcomes.


Unlike other tools, Brightaira provides “recommendations”, we call them “Parameterized Recommendations”. Where the AI engine determines the best recommendations and then decide the values within these recommendations that fit your organization. For example, available tools identify your negative sentiment, Brightaira’s AI engine on the other hand tells you what improves your sentiment and by which percentage you will probably improve when following the recommendations!



Try it for Free!

We believe AI should be available to all. Most of the available tools are very expensive and few organizations can afford to bear the cost.


We provide a ton of features with very affordable subscriptions fee that is suitable for many. You can also try the tool before you commit to any payment. TRY NOW.

 
 
 

Updated: Feb 12, 2022


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What is Big Data

Big data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analysed for insights that lead to better decisions and strategic business moves. Big Data refers to our ability to make sense of the vast amount of data that we generate every single second. In recent times, our world has become increasingly digitized, we produce more data than ever before. The amount of data in the world are simply exploding at the moment.

With the internet, more powerful computing and cheaper data storage helped to use data much better than ever before. Big Data means companies like Google can personalize our search results, Netflix and Amazon can understand our choices as a customer and recommend the right things for us. And we can use Big Data to even analyse the entire social media traffic around the world to spot trends.

Benefits of Big Data with AI

By bringing together big data and AI technology, companies can improve business performance and efficiency by:

  • Anticipating and capitalizing on emerging industry and market trends

  • Analyzing consumer behavior and automating customer segmentation

  • Personalizing and optimizing the performance of digital marketing campaigns

  • Using intelligent decision support systems fuelled by big data, AI, and predictive analytics

Realtime Examples of AI and Big Data in Business

Here are the examples of companies that use AI with Big Data and seen enormous success in their fields.

Case Study (a): Netflix – Big Data and AI Netflix uses AI and Big Data extensively and achieved great success as an organization. It has over 200 million subscribers around the world.

  • Generate Content: AI with big data helps Netflix in understanding consumers more and more granular level, thereby it helps Netflix to generate ‘content’ that matches the consumers taste to a large extent. Other competitors have a 40% success rate, whereas Netflix enjoys an 80% success rate.

  • Recommend Programmes: Netflix uses AI to recommend new movies and television programmes to consumers. 80% of what the consumers watch is driven by their AI recommendations. Netflix fine-tunes their algorithms in understanding the consumers and provides recommendations to the consumers about their programmes and movies.

  • Auto Generate Thumbnails: Netflix uses AI to auto-generate thumbnails. Consumers spend limited time choosing the films on seeing just the thumbnails for few seconds to minutes. Netflix understood the importance of thumbnails for consumers choosing their favourite programmes. Using Artificial Intelligence, thumbnails are generated dynamically based on the consumers’ interests.

  • Vary Streaming Speed: Netflix uses AI for Predicting the internet based on the consumers’ internet speed. AI algorithms help to scale up or scale down the streaming of movies based on the consumers’ real-time internet bandwidth.

  • Assist Pre-production: Netflix uses AI in pre-production activities. It helps to find location spots to shoot a movie (based on actors availability, actors location, etc)

  • Assist Post-production: Netflix uses AI widely in post-production activities as well. Although editing is manual, quality checks are driven by AI to avoid mistakes in post-production. There were several mistakes that happened due to negligence or lack of time, resources during post-production activities. But with the usage of AI algorithms, Netflix could eradicate these problems to a great extent.

Case Study (b): Disney (Theme Park and Cinemas) – Big Data and AI Disney uses Big Data and AI to give customers a more magical experience. Disney has always been a tech innovator in both Theme Park and in Cinemas to give the customer a wonderful experience.

  • Magic band: Disney offers magic band to its customers while they enter the theme park. Its kind of fitness watch which helps to open hotel room, allows the customers to pay. It has a GPS tracker in the band, which keeps tracking the customers where there are walking within Disney Theme Park. It is to ensure, where they are going within the park, which rides they are spending time, how much time they spend in restaurants.

  • Better Operational Management: It helps to schedule the workers to manage over crowding at one ride or at a single restaurant with in the park.

  • Better Customer Experience: Better management of crowd, giving proper assistance within the park gives the customer a better experience. They might direct the customers to other rides, other restaurants to avoid delay in one place.

  • Realtime Sentiment Analysis: Disney research team started using AI to understand real-time reactions when people watch in the live show or in the cinema. How they do is they are using ‘Machine Vision’ – AI coupled with a Camera, a night vision Camera looking at the audience. They do Sentiment analysis with the people in the show. Cameras will interpret the facial expressions by looking at how the people are responding to the shows or movies to see if they are sad, scared, having fun, etc. This would in turn help Disney to generate quality content based on the customers for their shows and movies.

Case Study (c): Big Data and AI with Motor Insurance Motor Insurance providers have started using AI with Big Data to provide a dynamic flexible insurance plan that will suit different customers based on their driving skills, ability and composure at different times.

  • Motor Insurance companies generally determine the premium based on the age of the vehicle. The insurance providers then started to understand the Customer based on how they drive by considering the age factor. This gave the perception a person aged 18 would drive rashly on comparing with a person aged 55 who will show maturity in driving.

  • Tracking Card: Motor Insurance providers started providing a tracking card to insert in the vehicle, which helps them to track and understand about the driving ability of the customer. This helped the provider to understand the customer better.

  • Mobile App: Now replacing the card with the mobile connected with GPS, it just needs the providers to install a mobile app within the customers mobile. This helps the providers to collect information about the customer driving. With the implementation of AI with Big Data, the providers can study the customer to a granular level. It helps the provider to understand how the customer is driving in a highway, during a rainy day, or on a hilly mountain road. Also, the question comes, they are people aged 18 who can drive better than the people with higher age. With the AI algorithms, over a period of time, the providers can understand each individual, how he is driving in the morning or in the late night, during a rainy day or during peak hours. Hence the data with the granular detail of the customer helps the Insurance providers to provide flexibility based on their driving skills not just merely on the age of the vehicle or the age of the customer.

Conclusion

It’s no hype that AI with big data are another set of high five technologies just to boast with for the IT giants. It has been used widely in several sectors and industries starting from big organizations to small business. The implementation of AI with Big Data in every industry has proved a great success and has helped the company business to a great extent. As said in the beginning, the world is exploding with data at the moment. Big Data with AI is really making sense of the huge data with the internet, more powerful computing and cheaper data storage.

 
 
 
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