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At a point in time, data-operated marketing, Artificial Intelligence, and Voice Search, engines had no such relevance in the technological world. They were considered some mere ambitious concepts that would not propagate accordingly. However, today these concepts have seen the light of success in its revolutionary way. In 2020, they are considered the most prioritized concepts of the business era.

Moreover, why would not the concepts be prioritized? After all, when it comes to competition in the business field, you must vividly adapt to the progressing technological advancement in the digital marketing platform. Let us discuss digital marketing trends that you absolutely cannot ignore in the year 2020.

  1. Artificial intelligence: If you are not aware of the advancement of technology today, then you are probably unaware of the fact that artificial intelligence is gradually dominating its way out in the year 2020.

From gaining a sustainable competitive advantage allowing enterprises to move into new sectors to cost-minimization and technology-driven products and services, AI is playing a pivotal role in business transformation.

Reasons for adopting AI trends in Digital Marketing 2020

In addition, AI can evaluate consumer buying behavior and patterns, and use business data to comprehend how customers search for products and services. So it is right to conclude that AI will soon be the driving force for a plethora of services in various business sectors like:

  • Product recommendations
  • Basic communications
  • Email personalization
  • Content creation
  • E-commerce transactions

Digital Marketing Trends

 

  1. Programmatic advertising: Programmatic advertising uses artificial intelligence to operate ad buying in a way that it can fetch an accurate audience for the brand. 
  2. Chatbots: This is one of the important aspects of digital marketing and it is going to remain so in the year 2020. This enables you to chat with your customers in real life at any hour of the day.
  3. Conversational marketing: This facilitates the one to one system of interaction between customers and marketers. Customers prefer this system as they get an immediate real-time response to their queries.
  4. Personalization: The one key to success in 2020 is to personalize your complete marketing system starting from products, contents, emails, etc.
  5. Video marketing: It is one of the important elements for marketing, and it is going to remain so for the next 5-10 years. It is very important to incorporate video marketing into your digital marketing strategies in the year 2020.
  6. Influencer marketing: It is a type of vocal or word-of-mouth marketing where key personalities are used to convey your products to a larger marketing area.
  7. Social media/messaging apps: The statistics of the messaging apps forecast the real value of it when it comes to marketing trends. Billions of people are on these social messaging apps, making it a great place for displaying your brands.
  8. Visual search: Visual search can help people get a greater experience. People can upload a picture of the specific thing they wanted to search and get instantaneous results.
  9. Micro-moments: To have the full advantage of this system in 2020, marketers need to be very careful and should place themselves in a way so that consumers could find whenever they are turning to a device to search for something at that moment. In other words, marketers have to be “be useful, be there, and be quick.”
  10. Smart speakers and voice search: As the amount of voice searches has increased considerably within the years, the marketers need to rethink their digital marketing strategies in 2020 and give more importance to voice search systems.
  11. Social-media stories: The popularity of this story concept redeemed from the Snapchat platform and now it has been popularized on Instagram, Facebook, and even YouTube. Therefore, marketers must consider this while promoting their brand online.
  12. Push notifications of browser: These push notifications are on the higher end of success and have been extensively used in marketing. 2019 has seen greater aspects of it as more than 85% of the online stores used it to engage customers.
  13. Content marketing over SEO: In 2020, Google rolled out with some new updates that confirmed that content marketing is much more effective than search engine optimization and thus content marketing continually dominates SEO.
  14. Search engine optimization (A/B split testing): When it comes to modernized marketing, everything renders about analysis and testing. By the use of the A/B testing, you can easily determine which versions are best complementing your business by driving the desired results. 
  15. Shoppable posts and social commerce: When both social media and e-commerce platforms are growing at an extensive rate, there is no wonder why marketers are using both for generating sales.
  16. Interactive content: Interactive content is one of the fastest-growing trends in digital marketing. In 2020, we are bound to experience dynamic and engaging content instead of traditional text-based boring content.
  17. Omnichannel marketing: It was one of the most popular buzzwords of 2019 and is most likely to be the one in 2020.
  18. Immersive technologies and augmented reality: It has been essentially predicted by Gartner that by 2020, almost 70% of the organizations are going to be under the influence of augmented reality and only 25% of them will deploy towards production.
  19. Augmented and predictive analytics: In the year 2020, digital marketing will come under the influence of this a lot more due to its significant use in lead scoring and in segmentation and personalization of an individual, which effectively helps marketers to improve the customer loyalty base.
  20. The rapid growth rate of geo-fencing: Geo-fencing is a great system to target customers as it uses the customer’s location for real-time targeting.
  21. Progressive web apps: They are websites that can be used as mobile apps. The year 2020 will bring in more and more Smartphone users and it is expected to reach up to 2.87 billion by this year.
  22. User-generated content: It is a Strong resource for marketers who want to enter the millennial markets. The year 2020 marketers need to have this system to grow.
  23. Blockchain technology: By 2020, we will see the following trends in the Blockchain: tracking of media buys, elevating transparency, handling of social impressions, pinpointing the target, protection of personal data, provenance, and authentication.
  24. Quantum computing: A new technology is significantly based on Quantum Physics.

Honorable mention:

  • Deep learning and larger data
  • Automation
  • Smart auction of google ads
  • The position zero in SERP
  • Branding
  • Superior Analytics
  • 5G technology
  • Secluded marketing
  • Security of the website
  • IoT advertising
  • Long-form content
  • Keyword search
  • Structured data
  • Search engines
  • Voice marketing

Conclusion

In these recent times, everything we can think of is online. So taking business and marketing to the web is a tactical approach that can be proved profitable. Digital marketing is a dynamic platform with a constant employment rate and even more. Recently there have been many new job openings in this field. Therefore, the digital marketing trends mentioned above are very essential for any marketer to take their business to the next level.

 

To be honest, designing business marketing campaigns for existing customers is as difficult as nailing jelly to a tree. That’s given.
To accomplish this feat of tough analysis, access to a list of customers, email addresses, and purchase data is imperative, but the tricky part remains unattended- sending meaningful insights that will boost a customer’s lifetime value and trigger a repeated purchase.

This trick of accurately targeting customers has been cracked by big enterprises with the help of in-house Data Science teams using a particular approach. The name of their approach is- Market Basket Analysis (MBA).
It is one of the key approaches adopted by renowned retailers to unravel the link between items. One of the basic principles of this approach is to track the combination of items that occur together repeatedly in the transactions.
In simple words, it enables retailers to determine the relationship between the items that consumers purchase. Let’s dig deep for a better understanding.

At the core

The very base of MBA, popularly known as Affinity Analysis, is depended on Data Mining, which uses Association Rule Learning to determine the bond between customers and the attributes associated with them.

The more common and stronger a relationship is, the quicker you can put your customers into segments for future analysis. All that is needed for this initiative is customer and order data.

A scenario– In a grocery store, there are numerous products, out of which consumers can lay their hands on any particular group of things. Say Peanut butter and jelly, cream cheese and turkey, etc. Using Market Basket Analysis on the grocery store data, it will be a piece of cake to determine which products are brought together by customers. Adding a feather in its cap is- discovering new bonds between customers and newer product combinations.

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How to make your Season Sales more efficient? Only AI has the answer

To comprehend the relationship between Customer Buying Behavior and MBA in detail, read on.

Comprehending Customer Buying Behavior using MBA

With MBA comes the good news of unearthing the connections between the purchasing pattern of customers, by determining the products or menu items that appear frequently in transactions.

Smart retailers can evaluate this relationship between the products, which consumers purchase and can use this data to come up with new products or pricing models for maximum revenue.

Here are some smart ways to make use of such insights from MBA:

Cross Selling - Up sell - Market Basket Analysis

  • Cross-Sell: Group products which customers buy often from the store
  • Marketing promotions: Focus marketing campaigns to customers and lure them to buy products for an item recently bought
  • Web stores- Propose associated items that are frequently purchased together (“Customers who purchased this product, also viewed this product”)

To read the maximum benefits of this analysis, hiring the services of an expert in the field is the only option.

How SPIN’s MBA Analysis expertise helps

It comes as no surprise that MBA is applied to different segments of the retail sector to pump up sales and open new streams of revenue sources by determining the requirements of the customer and making purchase offers to them.

Banking on this theory, SPIN uses MBA to help its clients with:

Cross-Selling: A sales technique that enables the seller to suggest a related product to a customer after the first purchase is made. With SPIN’s MBA, retailers can comprehend consumer behavior and pitch the right product for cross-selling.Up Sell Cross Sell Market Strategy

Product Placement: It is a technique to place complementary and substitute goods together for the customer to buy them together. Using SPIN’s MBA, retailers can determine the goods, which a customer is more likely to buy together.

Detection of fraud: MBA contains credit card usage details and it can be used to determine the purchasing behavior to detect fraud possibility. SPIN’s MBA will prevent your retailer business from such adversities too.

Customer Behavior: SPIN’s MBA helps to comprehend customer behavior under a host of different conditions, enabling the retailer to determine the connection between two products, which people purchase, and get the knowledge of the customer’s buying behavior.

SPIN’s MBA is the combo of AI and ML

Businesses want to evaluate the different angles of customer behavior inside a store. With the right data sets to determine customer behavior of retail stores, businesses can categorize data to define the :

  1. Right product association
  2. Trip types
  3. Point of sale and marketing

Artificial Intelligence and Machine Learning

After analysis of the consumer behavior inside a retailer store, AI and ML techniques powered by SPIN Strategy algorithms are applied to reap the following benefits for the retail business:

  1. Develop lucrative combo offers
  2. Place associate products together in the store
  3. Customize the layout of the eCommerce site catalog
  4. Manage inventory based on the products with better demand
  5. Categorize different shopping trips to generate the best shopping experience
  6. Create customer profiling and apply segmentation using buying pattern
  7. Determining the best product association

To wrap it up

Market Basket Analysis is used by some of the biggest companies in the world to make informed and strategic business decisions. 

Here at SPIN Strategy, our professionals can help you perform such an analysis on your customer base to drive your market growth and design your product.

Interested in exploring MBA? Visit: https://www.spinanalyticsandstrategy.com/

Artificial Intelligence – Leading the way towards global development!

With the world rapidly evolving, customers have become almost equivalent to business owners dictating the shopping terms, sales funnel, marketing efforts, etc. As per their needs, customers decide:

  • How to shop
  • Where to shop, and
  • How to proceed with the transactions-online or offline

Along with adapting these changes in customer aspirations, organizations also need to redefine business operations for every industry to emerge more customer-centric and tailor-made as per customer needs.

Reality CheckCustomer-centricity is not an out-of-the-box topic for organizations, principally for those trying to set a benchmark for client satisfaction.

Before we get further, let’s get an in-depth understanding of what a Customer-Centric company is.

What is a Customer-centric company?

In business terms, being a customer-centric company means offering unprecedented customer experiences right from awareness to purchasing, and finally post-purchase stage.

Customer Centric Business Structure 2020

For a customer-centric company, it is a mandate to execute business operations that stimulates positive customer experiences, prior and post-sales conclusion. This assures to uphold the culture of repeating customers, and boosts consumer loyalty for increased profits.

Does your business is in need of it?

Business needs Customer-centricity: Why

Market hypothesize confirms that businesses that apply customer-centric strategies encounter a 55% increase in profits, year by year. For such businesses, customer-centricity is more than mere words on a paper and goes beyond employee meetings or customer surveys.

If the target is to improve the business value and be in sync with the changing trends, incorporating customer-centric strategies is the key.

As per the core principle of customer-centricity, every organization in any industry requires a robust foundation in 1) leadership and 2) strategy, and the poised use of 3) people, 4) platforms and 5) processes.

How to be a customer-centric business?

Customer-centricity commences with a company’s culture and commitment to customer’s success.

Here is how your organization can turn into a fully-fledged customer-centric business.

Customer Centric Business Strategy

1. Predict customer requirements

Anticipating the market’s future needs is a game-changing business move. To be customer-centric, it is imperative for companies to anticipate customer needs and provide helpful suggestions accordingly.

2. Compile customer feedback

Frequent and regular communication with customers is the key to successful customer-centricity. Thanks to the digital transformation of the world, there are countless encounters to accumulate customer feedback like emails, chat, In-app messages, SMS, FB messenger, etc.

3. Convenient customer support

Contacting the support team of a digitally built business is the most difficult task. Easy access to customer support builds rapport and trust, laying the foundation for long-term business relationships.

4. Deliver proactive customer service

Providing customers with added value beyond the point of purchase, like proactive customer service- resources to customers to solve minor problems independently, is the key differentiator.

5. Move beyond purchase

Only with added benefits that extend beyond the point of purchase can old customers be motivated to  buy again, and create a memorable experience.

 

Measuring customer-centric success is crucial: 

Customer Centric Business Strategy
Customer Centric Business Strategy

To measure the success of a customer-centric business, taking into account the following top three significant customer metrics is fundamental:

Net Promoter Score

Are you happy with the products/services?

NPS that focuses on unraveling customer loyalty uses the answer to define the success of customer-centricity.

Whenever a client answers to this question, the response is segregated into certain predefined criteria.

 Net Score Business

Promoters (9-10) – Such customers love the product/service and are quite likely to refer it. Customers who rate your product/service a 9 or 10 have high customer lifetime value and are indefinitely repeat customers.

Passives (7-8) – Such customers who rate your product/service a 7 or 8 are simply happy being a client, however, they are more prone to switching to a competitor in case of a better and inexpensive product.

Detractors (0-6) – Customers providing such ranking are unhappy with the product/service, and are more prone to damaging brand reputation.

Bottom line- The more Promoters a business has, the better the growth it experiences.

Churn Rate

Procuring new clients on a frequent basis puts most organizations in a quandary. Thus, more business is investing in retaining existing clients instead of chasing more fresh leads. Here’ why:

  • Procuring new clients, compared to existing clients, increases the cost up to 5 times.
  • Minimum 2% hike in customer retention is equivalent to cost-cutting by 10%.
  • On an average, companies lose around 10% of their customer base annually.

Note: Companies with a higher retention rate grow faster.

Customer Lifetime Value (CLV)

For any growing business, the customer base is one of the most valuable assets.

With CLV, the revenue collected from such clients during their customer lifetime, starting from the first purchase until the time transactions stop is measured.

With the help of CLV final calculations, it is easy to comprehend why a business should keep investing in customers.

Concluding thoughts

It is no news that businesses are reaching out to different ways to incorporate more customer-centric strategies in their approach.

Any organization that has a lack of customer data and priorities revenue over customer needs still has some catching up to do to sustain in the 21st– century business world.

Introducing the customer-centric brand culture is undoubtedly the best route for businesses to align leaders’ choices with the mindset of the team and cultivate the values. To successfully apply the customer-centric strategy, this culture must be in sync with other business strategies.

At SPIN, we maintain robust individual contact profiles and useful CLV insights and purchase likelihood tools that can help your esteemed organization to be customer-centric successfully, and market smarter.

Visit today: https://www.spinanalyticsandstrategy.com/

 

PREDICTIVE MODELS 2020

Be more accurate towards forecasting your data. Know the hidden patterns within your data to explain statistical abnormalities and explore the relation behind the unexpected Customer Patterns and sudden fluctuations in the audience segmentation metrics. 

Here are a few Predictive Models that make it happen:

1. CUSTOMER SEGMENTATION: 

Dividing customers into groups based on common characteristics is Customer Segmentation.  

Knowing your customers and targeting them in the most relevant way to boost Customer Retention and Customer Satisfaction is the primary motive for any business.

Get Answers for every doubt you have related to your customers using this Model:

  •  Know your customer requirement before launching a new product
  • Target specific Customer Branding
  • Rebrand new customers

Customer Demographics, Customer Buying Behavior, Customer Interests, and Customer Profiling are some of the additional benefits of the Customer Segmentation model that businesses look forward too.

2. CROSS SELL AND UP SELL MODELS:

Looking for quick wins and easy growth?

Upselling and cross-selling are considered to be the two most effective ways to boost revenues for retailers. Upsell is used when business owners want to convince their customers to purchase a more expensive  product/ service, while salespeople use cross-sell to encourage consumers to buy more products based on instinct.

Here is the strategy used by Cross-Sell and Up-Sell model:

  • Loyal Clients Feedback First
  • Business Quarterly Reviews
  • Gathering testimonials and Case studies
  • Blog sharing
  • Trial and error
  • Time to time discounts and Offers
  • Know your Needs
  • Employee Retention

3. CHURN MODELS:

Customer Churn Prediction

Churn Rate defines the percentage of Customer Retention for your products/services. Customer Churn prediction tasks will often use customer data to determine:

  •  Time spent on a company website
  •  Products/ services  purchased
  •  Demographic information of users
  •  Links clicked
  •  Text analysis of product reviews

Types of churn Models:

  1. Define Metrics with Consumer data
  2. Shifting insights based on Outputs
  3. Adding machine Learning to Churn

4. SENTIMENT ANALYSIS:

Discover Customer emotional connect towards a product/service and boost Brand Reputation Management with Sentiment Analysis.

Sentiment analysis and opinion mining find numerous applications in e-commerce, marketing, advertising, politics, and research, with:

  • Text Polarity
  • Sentiment ranking
  • Feature Sentiment Analysis

5. PRICE PLANNING AND ANALYSIS:

It is important to analyze the pricing situation to develop a Price planning and Analysis strategy to:

  • Evaluate new product ideas
  • Test marketing
  • Introduce strategy
  • Add Positioning               

Analyzing the pricing strategy benefits the business by:

  1. Establishing the responsiveness of the market to price
  2. Determining cost
  3. Analyzing competition
  4. Assessing legal constraints

6. CUSTOMER SPENDING PATTERN ANALYSIS: 

Customer spending patterns can be divided into regular spend pattern and lifestyle spend patterns.

  • Regular spending  means basic necessities of life, 
  • Lifestyle spending means spending on a computer, internet, car, cell phone, etc.
  1. Cultural
  2. Social
  3. Psychological
  4. Personal

7. PRODUCT RECOMMENDATION:

Product recommendations will work for ECommerce Businesses where there are unfriendly sales assistants to help customers with each step of their shopping journey.

Product recommendation engines fall into 2 main categories: 

  1. Unpersonalized
  2. Personalized

8. IMPACT ANALYSIS OF SALES PROMOTION:

What are the promotional offers that has the highest impact at present?  This question is relevant for every product/service-based business.

Promotional analysis is a technique of analyzing success or failure of a promotion using past time series data. 

Types of Promotion Analysis include:

  1. Quantity/Product concession
  2. Price discount
  3. Ads
  4. Shipping promotion

9. CONSUMER CHOICE MODEL:

The consumer choice model is used to determine the buying decisions for several commodities with different results. Such models take into consideration different families, classes, attitudes, etc.

The basic steps for Consumer Choice Model include:

  1. Recognition
  2. Information search
  3. Alternative evaluation
  4. Purchase decision
  5. Post-purchase behavior

10. AD OPTIMIZATION

Some ads do well than others and generate more clicks, revenue, conversions, higher conversion ratio, etc. Based on these features, you can display the better performing ads more and show a red flag to the poor ones to boost the ROI.

The Ad Optimization models operate by:

  • Adding a call-to-action model
  • Adding emotional content
  • Using Ad Extensions
  • Trying dynamic keyword insertion

11. PROPENSITY MODEL

The method of predicting the possibility that visitors, customers, or leads to conduct certain actions are termed as Propensity Analysis.

Based on Propensity modeling, marketing teams forecast the likelihood of whether a lead will convert to a customer, or will churn. Add to it, propensity modeling also helps to predict whether an email recipient will unsubscribe or not.

Here is how Propensity Modeling works:

  • Determining the features
  • Preparing the propensity model
  • Calculating your Propensity scores

12. TIME SERIES AND CASUAL ANALYSIS:

Time Series Analysis is used to clarify, track, and forecast casualty behaviors of customers. Whatever time-based patterns business experiences, Time Series Analysis can be used to determine it.

Time Series models can be applied to the following applications:

  • Business- Web traffic, Supply Chain, etc.
  • Finance- Stock option, econometrics, etc.

13.FRAUD MANAGEMENT AND PREVENTION:

Spotting potentially fraudulent behavior and identifying unusual patterns of behavior consistent is termed as Fraud Management and Prevention.

Fraud Prevention models provide:

  • Expert alert scenarios
  • Real-time integration
  • Quick roll-out
  • Audited workflow and case management
  • High performing testing tools

In an era of machines and Artificial Intelligence, the traditional form of banking has taken the back seat, when compared with tech-savvy Fintech players of the industry who are keen to adapt latest technologies to keep up.

As per market experts, it goes without saying that AI will empower Banking Services, redefining operations by innovating products and services beyond the conventional norm. This eventually perks up customer experiences. Leveraging advanced technologies, human workers will be replaced with sophisticated algorithms.

Such a competitive edge can only be achieved by banking corporations by embracing AI and weaving it into strategic business decisions for maximum profits. 

AI can double Business Profits

AI professionals quote; there are three primary ways the introduction of AI in the Banking Sector can shoot business profits.

Here they go:

  • Enhancing contemporary Profits and Loss levers
  • Identifying new growth patterns
  • Delivering the Digital bank

But the question is: How AI can achieve this objective? The answer to it is by:

  • Profiling and Customer Segmentation– Being aware of the financial profile of all the customers helps banks to jack up the expenditure and income for next month, and maximize revenue.
  • Customer Spending Pattern Analysis- Typically, banks have adequate data about a customer’s flow of income every month, net savings and utility expenses. With the help of this model, banks can conduct a risk assessment, loan screening, cross selling of financial products, and mortgage evaluation.
  • Evaluating Creditworthiness- Determining whether an individual is likely to be a defaulter and estimating the amount that can be offered to him/her.
  • Transaction Channel Identification- With the help of AI, banks can determine if a customer is likely to keep or withdraw money on payday. The latter customers can be pitched for short-term investments.

All the above-mentioned objectives have one thing in common- SPIN Strategy AI Models.

SPIN’s AI models are banking Operation-Focused

At SPIN, we provide a range of AI and ML learning tools for a host of operational applications for financial institutions. Such tools include:

1. Risk assessment, compliance & reporting 

Comprehends the spending pattern and analyzes previous credit history to assess the risk of issuing a loan to a customer.

2. Sentiment Analysis: 

Customer view and market rumors play a significant role in business, and with NLP it is easy to comprehend customer sentiment and its impact on the enterprise.

3. Propensity Modeling

Uses historical data to make business predictions by directing consumers to the right messages and website locations.

If that’s not all, here are a few factors to conclude the fact that SPIN  Models are a boon for the banking sector.

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SPIN for Banking Services: Here is why

  1. Communication: We keep our customers in the loop with necessary and crisp data, perfecting the art of delivering the right solution to the right clients at the right time.
  2. Minimal expenses: No fluctuating invoice rates for our clients. We maintain a simple flat monthly rate.
  3. Rate: Simple monthly pricing for your business requirements at easy rates.
  4. Experience:  Maintaining optimum performance standards, our experts use AI-models for Data Integration, Conversion Optimization, Data Analysis, etc.
  5. Data Integration: We combine data from multiple digital marketing platforms to prepare customized reports to generate a holistic understanding of your brand’s ROI and growth.
  6. Predict Churn: Using AI and ML, SPIN identifies segments of the customer base who are about to leave you for your competitor brand.

The result of using SPIN AI Models for Banking Decisions- Improved decision making for credit and loans.

Here is a real-life scenario- Case Study

The Client-  The client offers financial services and technical support in a bid to increase productivity, boost innovation, and add economic integration. 

The Issue– The bank officials have diverse knowledge on various topics, and have shaped themselves as SMEs of certain topics. They share their knowledge from different geographical locations. The client wanted a single integrated knowledge management platform for individuals to reach out to these SMEs for a certain project in hand.

The Solution- SPIN worked with the client to deploy a cognitive computing application that would include a virtual agent to comprehend Natural Language request inputs and utilizes cognitive deductions to answer the queries.

In a bid to simulate human-like conversations between the systems and the users, SPIN leveraged Advanced Text Analytics including entity extraction, keyword extraction, emotion analysis, sentiment analysis, etc. 

The Result- The bank now has the faith that productivity across the globe will hit the roof due to the easy availability of SMEs. This will boost operational efficiency by 30%-40% and expand cross-broader collaboration and employee management too.

To conclude with

We are more than happy to help Banking Organizations with AI and Data Analytics services. Guaranteeing a solution that caters to clients’ needs and budget, at SPIN we ensure to provide excellent value for businesses. 

For more info, visit: https://www.spinanalyticsandstrategy.com/

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In the true sense, Farming is by far one of the oldest lines of work in the world.

But, with the passage of millennia, Humanity has come a long way and so did agriculture. From conventional methods to grow crops to the usage of AI in Agriculture, Humanity has indeed taken a big leap.But with land getting in short supply and population growing by leaps and bounds, using creative methods to produce crops and boost productivity in limited space has become the need of the hour. 

Change has stepped in. And this can be testified by the fact that the worldwide agriculture industry which is roughly estimated to be around $5 trillion, is stepping in the shoes of other sectors, shifting to what is known as Precision Farming

For instance, adopting AI technologies to reap healthy crops, monitor soil, control pests, accumulate data for farmers etc. and eventually perk up a number of agriculture-related errands in the food supply chain.

Artificial Intelligence in Farming

Digital Agriculture: Farmers are using AI to increase crop yields

Artificial intelligence holds the promise of driving an agricultural revolution at a time when the world must produce more food using fewer resources.

Artificial Intelligence has various applications in agriculture ranging from rural automatons, facial acknowledgment, computerized water system frameworks, and driver less tractors. These applications are done in relationship with an alternate sort of sensors, GPS frameworks, radars, and other cutting edge contraptions dependent on AI.

Innovative progressions and the modernization of GPS are making ranchers and the agriculture specialist co-ops anticipate that additional upgrades will increase the profitability.Increasing adoption of the mechanical technology and IoT gadgets in agriculture is additionally assessed to drive the AI in agriculture.

Agriculture is slowly becoming digital and AI in agriculture is emerging in three major categories, (i) agricultural robotics, (ii) soil and crop monitoring, and (iii) predictive analytics.

Agricultural Robots – Companies are developing and programming autonomous robots to handle essential agricultural tasks such as harvesting crops at a higher volume and faster pace than human laborers.

Crop and Soil Monitoring – Companies are leveraging computer vision and deep-learning algorithms to process data captured by drones and/or software-based technology to monitor crop and soil health.

Predictive Analytics – Machine learning models are being developed to track and predict various environmental impacts on crop yield such as weather changes.AI With Agriculture Farming

How Analytics and AI steps in actually

Intelligent farming practices that have eventually transformed into knowledge-based agriculture, increases production levels and product quality to significant numbers. 

With trained professionals in this art, companies like SPIN Strategy extracts insights from numerous data sources that are integrated into an Advanced Big Data Framework with data analysis decision-making, and automated data recording. 

Result- Customized data for better plant health.

At SPIN, with the combination of smart farming and AI, we assemble, analyze, and digitize massive amounts of data to aid farmers to optimize their production systems. And, that’s why we like to be termed as the Farmer’s Little Hand.

With the use of technology, we:

  • Determine the ripeness of the crop
  • Help farmers preserve water
  • Customize production

Let’s dig deep to understand how ML and AI make a difference in Smart Farming using IoT.

Role of Artificial Intelligence in Agriculture

The agricultural industry is just like any other industry beginning to show interest in implementing the best-in-class technologies to save on resources and create more efficient processes. Agriculture is responsible for the survival of human beings, and the industry has made steady technological improvements in the last few years.

IoT in Smart Farming

How SPIN’s ML and AI programs make the difference in Agriculture: 

Machine Learning in Farming: 

Provides faster and precise results by evaluating the Leaf Vein Morphology that has more data about the leaf properties.

Artificial Intelligence in Farming: 

Uses algorithms and previous field data to determine crop performance in different environments, and builds a Probability Model to forecast the genes beneficial for the plant.

Here is a detailed overview, how SPIN’s AI programs turn the tables for agriculture:

1 . Water Management:

An AI-based application that can be connected with more successful use of irrigation systems and forecasting of daily dew point temperature, which is the base to determine any weather phenomena and analyze evaporation and transpiration.

Water Management with AI

2. Yield Prediction: 

Moving beyond the traditional prediction of historical data, SPIN incorporates computer vision technologies to supply data on the go and conducts a thorough multidimensional analysis of weather, crops, economic conditions, etc. to reap the maximum benefit of the yield for farmers and the population.

Yield Production

3. Crop Quality:

The precise detection and categorization of the crop quality can shoot up the product price and cut down waste. Compared to human counterparts, machines avoid meaningless data to determine the quality of the crops and any possible anomalies.

Soil Management

4. Disease Detection:

At SPIN, we evaluate field images with Conventional Neural Networks to classify pests and diseases, track agro-technical activities, and gather data. To be more efficient, this approach needs more pesticides that lead to huge environmental expenses. ML is used as a general agriculture management to determine diseases and cut those costs.

Disease Detection

5. Monitoring Crop’s health: 

Hyper spectral imaging, together with sensing techniques and 3D laser scanning are vital to establish crop metrics across the land. SPIN crop health monitoring agent has the potential to change farmland monitoring by farmers and can significantly cut down on the effort. 

Monitoring crop’s health

How SPIN Contributes to Smart Farming

Confirmation and extensive testing of emerging AI applications in the Agriculture sector is estimated to be quite vital, since agriculture is affected by environmental factors that cannot be tamed, unlike other sectors where the risk is easy to predict.

At SPIN, we ensure a steady adoption of AI in agriculture with the help of Image Sensor Technology that helps in:

  • Real-time monitoring, analysis, and control of pest & disease
  • Pollination, Phrenology, Fertilization, Irrigation
  • Pollination, Phrenology, Fertilization, and Agri-Technical activities
  • Monitor and forecast yield performance in real-time to optimize results
  • Using Support Vector Machines to predict yield and crop quality
  • Using Artificial Neural Networks for crop management and weed detection

Scenario

Issue-One of our clients, a Colorado-based organization, wanted a preventive measure for defective crops, and optimize the potential for healthy crop production.

Solution– The trained AI professionals at SPIN conducted a comprehensive Soil Analysis and developed a system that will use Machine Learning to deliver clients with an idea of the soil’s strength and weakness. This way defective crop production could be prevented to a significant degree.

To conclude with

Artificial Intelligence and Farming have the potential to pave the way for an agricultural revolution, especially when the world needs more food production with limited resources.

As per the UN Food and Agriculture Organization, the population will hit the roof by 2 billion by 2050. However, experts are of the notion that only 4% of the additional land will fall under cultivation category. In tune with this, the use of the latest technology to do smart farming still takes the front seat.

AI-Powered solution will enable farmers to do more with limited resources and produce the finest quality of crops that amazes even the producer.

Need professional guidance to reap the benefits of using AI in farming? Visit SPIN Strategy today: https://www.spinanalyticsandstrategy.com/