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Data Analytics will be the major game-changer for eCommerce 4.0 in 2019

Going by market analysis, Data Analytics has played a vital role in the e-Commerce ecosystem and will continue to be the major game-changer.

Thanks to the rising need in a short period of time, the frequent use of Data Analytics in all major departments like Marketing, IT, Operations, etc. became crucial to process potential clients and market data to adopt strategic strategies that will eventually lead to providing services successfully.

That’s why experts say:

“Without Data, you are just another person with an opinion”

Numbers speak it all

  • More than 75% of companies using Predictive Analytics data experienced higher sales
  • 66% of customers feel annoyed when irrelevant offers are sent to them due to lack of relevant data
  • 65% increase in business margins with the use of relevant data
  • 48% of shoppers are more likely to shop on personalized recommendations offers

Data Analytics a Boon for E commerce 4.0

It is no Rocket Science to analyze the fact that customer demand will evolve rapidly in the days to come, and this change will be responded by sellers using AI in a bid to comprehend the demand or what customers would want.

Here are the top 4 ways how Data Analytics will respond to the changing dynamics of eCommerce 4.0 for good:

1. Improved Shopping Pattern observation- Using Big Data Analytics can help sellers to available at the moment, demand spike, etc.

2. Anticipate future operation strategies– Using Big Data Analytics helps sellers manage business operations better, be it inventory, demand forecasting, supply chain, pricing or sales strategies. 

Also, using Big Data Case studies will give a seller a thorough understanding of different business operations and the inevitable problems they involve.

3. More spotlight on Micro-Moments– Successful sellers can leverage this hottest trend for quick actions like- I want to buy, I want to know, I want to go, etc. to predict customer tendencies and action patterns.

4. Improved Online Payment functions– More than 51% of e-Commerce sales are done via mobile platforms as per statistics. This means online payment options need to be more secure and safe than ever before. 

Using Big Data Analytics can help the detection of fraudulent activities and securing of payment gateway by centralizing it into one platform and making it easy for clients.

Analyzing massive Data Sets will not only do wonders for e-Commerce businesses but customers too. 

E-Commerce companies will use data-driven insights to enhance the way customer demands are met and will revolutionize the buying and selling ecosystem.

If you too are a fan of Data Analytics and understand its relevance in your business, get in touch with the professionals at SPIN Strategy and welcome strategic planning and increased ROI for your business, today.Visit: SPIN 

 

Social Media Marketing Tactics 2019

It is not the planning that affects your journey; it is the mistakes you make.

Same is the case with Social Media Marketing and the evident mistakes synonymous to it. Ask any social media marketer, and the plan to boost business engagement with the target audience is ready with them. But they never take into account the top 4 mistakes that can turn a campaign into a failure.

Only with a planned strategic approach that can be managed and optimized, you can mold your digital marketing activities 2019 to reap lucrative returns on your investments. But to do so, you need to dodge the common pitfalls most brands usually make. 

Here is a gist of the top 5 common social media marketing mistakes to look out for:

1. Wrong KPI measurement

Often, it has been observed that social media marketers measure the success of a business campaign with the number of followers on Twitter or fans on Facebook. This is a wrong Key Performance Indicator measurement. 

The focus should be on the measuring of the impact of the social media marketing efforts on business, rather than the number of followers.

2.  Assuming all Social Media Platforms are equal

All social media networks are equal. Assuming such a notion is one of the biggest mistakes a social media marketer makes and this approach is counter-productive and ineffective. 

Every social media network has its own set of customs and audience that requires customized content and a social media marketer needs to account such aspects.

3. Don’t talk only about your business

Nobody likes a person who only talks about himself. Same is the case with certain companies who only talk about their events, news, projects, services, etc. and not everyone likes it.

To reach the pinnacle of social media, you need to speak the language of the audience and understand what they wish to hear by posting relevant and diverse content for them.

4. Social Media Policy is missing

One of the biggest failures of social media marketing campaigns these days is the lack of a company-wide social media policy. Irrespective of the fact who manages your social media accounts, you cannot afford to miss out a widely accepted policy, and your content should not be offensive, racist, or hurt religious sentiments. 

The bottom line

As per market surveys, most of the businesses these days fail to incorporate social media successfully in their marketing endeavors and often follow the trend of others ending with an unsatisfactory result. 

So, ensure you put these tips into practice and never miss out on them, and your social media campaigns will not only grow your customer base but will also skyrocket your ROI on your investments.

If you are still unsure how to avoid all these mistakes, better to hire the services of the best in the industry, like SPIN Strategy. Visit: https://www.spinanalyticsandstrategy.com/

 

Artificial Intelligence - Leading the way towards global development

Humans have already been taken a huge leap towards an advanced future while copying human intelligence and marking it up with machines. 

Artificial Intelligence and Machine Learning bring great potential to change several situations that the world is facing today. 

While the technology has embarked it’s impact outcomes to both general use and industrial use, Artificial Intelligence’s is a much-trusted solution to fight against terrorism globally.

Innovation has always helped humankind take a step ahead in the future and transfer knowledge into applications. 

Machine automation along with a replica of the human intelligence to understand, learn and react has revolutionized industrial operations and a lot more. We very well know the fact that data is the fuel that drives most of the daily operations over the internet and into our daily lives. With more data, machines now can learn and adapt to its users.

In a recent conference at Minsk, organized by the United Nations Office of Counter-Terrorism (UNOCT) and Belarus, Artificial Intelligence was considered to be a cutting-edge solution for dealing with global terrorism. Vladimir Voronezh, Under-Secretary-General for the UN Counter-Terrorism Office, declared that the international community is utilizing artificial intelligence and machine learning capabilities to track down criminal and terrorism data globally.

The recent trends in Artificial Intelligence find its way to different sectors but mostly are leveraged by the government and law enforcement bodies to deal with national threats. This is itself a great leap for the technology. Here is a list of four latest trends that are today widely accepted by business owners, the government, security agencies, etc.

  1. People Analytics: Pouring on the fuel of data, artificial intelligence can do miraculous things. Through AI, business and organizations can harness the data of people enrolled with them for any targeted campaign.
  2. Algorithmic Website Personalization: Ever noticed how YouTube personalizes its home page as based on what you like or prefer to watch? This is all AI and machine learning. 
  3. Automated Customer Service: Retrieving customer data can help businesses provide the most relevant marketing campaigns, product display and a lot more. AI will help in customizing the customer experience. 
  4. Automated Resource Management: AI learns how to organize and allocate their subjects.

Given the present scenario, it is imperative to boost the exchange of expert knowledge on technologies such as Synthetic Biology, 3D Printing, Robotics, the synthesis of the human face

Nanotechnology, etc. to identify risks before-hand and respond in a jiffy.

At SPIN Strategy, we have experts of Robotics Process Automation, AI, and Machine Learning who can not only guide you in these complicated routes of business but also aid you in meeting your quest.

Before we dig deep into the nuts and bolts of MLP (Multilayer Perceptron), it is imperative to get the hang of neural network, to understand how it helps businesses get a major face lift.

Although the concept of the neural network is not likely to raise too many eyebrows out of ignorance, still people typically associate scientists conducting neurological research, with the term. In reality, a neural network is nothing but a smart system, which is steered by Artificial Intelligence (AI).

The most frequently used neural network these days, from the perspective of business, is MLP (Multilayer Perceptron). This neural network captures the most complex data and presents it in the simplest form, with the help of historical data.

Point to note- More than an individual, it’s the companies that get benefited out of MLP.

Companies prefer using MLP for business

If we go by market reports, companies use MLP in ways more than one, based on their business model. For instance, LinkedIn uses it to detect spam, while other companies use it to locate better products for it clients.

Add to it, MLP neural networks provide marketers with significant insights regarding the performance of the marketing initiatives.

Some of the uses of MLP by big shots of the industry include:

  • Amazon-use MLP for recommendation purposes
  • Facebook-use it for face recognition
  • Google has been using it-in YouTube, Google Cloud, Video Intelligence, etc.

This overstates the fact that MLP is typically good for business. Read on to get convinced how MLP can benefit your business in ways you have not yet imagined.

Top 4 benefits of using MLP in business

AI and its application is prevalent everywhere. A smart business leader can never overlook the impact of AI and its applications, if his/her prime objective is to cope up with the changing business landscape.

Here are the top 4 reasons why MLP is a must in your business to cross its boundaries of growth.

Identifying patterns in images

With machines now able to identify images, business has taken a big leap, and almost every company worldwide, require pattern recognition facility.

Recommendation option

Most online companies make money via the recommendation of products/services, like Amazon, Netflix, Walmart and many more. 

The fact that the use of recommendation engines opens doors for targeted and loyal customers along with increased sales, makes it all the more important. Now imagine these recommendation models being modified by more intelligent machine learning with the use of neural networks- Yes! more loyal customers and more sales.

Avoiding customer churning

Churn rate (percentage of customers who cease to use a product/service), is something every growing organization is worried of. For some, shrinking churn rate showcases a positive impact on the revenue chart.

Provided that a business is equipped with rich customer data, machine learning models together with MLP can help point out the complex usage patterns and find out the churning customers.

Advanced sales predictions

No matter businesses do not like to forecast sales, the fact that customers can be fickle and their preferences change, cannot be neglected. In tune with this, to tap into the new trends and moods of the customers, companies make predictions, which is highly time-consuming and hardly ever accurate.

If MLP is used to analyze huge data and make specific predictions, this could change the sales numbers of companies, in a good way.

The promising future of business with MLP

In the quest to come up with an efficient replicate of the human brain, MLP is a great step forward.

Covering the most arduous business area, MLP is the best tool for pattern recognition. On account of its increasing popularity, in the last few years a number of companies have invested in an artificial neural network. This a significant step to put an end to numerous business problems. 

If put to good use, MLP can bring significant change in digital marketing, healthcare, translation service, trading, etc. 

Have you found the relevance of MLP with your line of business? Then contact the professionals at SPIN Strategy who can guide you how to make the most of this neural network for business. 

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

How can Inferential Analytics help business with target customers?

 

Say, you wish to know the average salary of a data scientist professional of a particular region. What are the possible options you can think of?

  1. You personally meet with every data scientist of that region and make a note of his or her salary.
  2. You hand pick few professionals of that region and calculate the average salary.

Although the first method is not impossible, it is a Herculean task indeed, which will consume a lot of resource and time. And keeping in mind the swift moves of companies these days, easy and quick solution is not just preferred but a priority too.

So, what method should be used to figure out the average salary of the data scientist of that area? 

The answer is Inferential Statistics.

For starters, and to put it simply for all, Inferential Analytics is typically designed to draw assumptions beyond the present data available. 

How it works-By taking a random sample of data from a particular set of population and making assumptions and inferences about the people.

But how can this demographic analysis help a business meet its sales targets? Read on to know more.

How to grow business with Inferential Statistics?

With time, the marketplace shifts and evolves, and so does the list of your clients. 

So, it’s time to get ahead of the curve and get a step ahead in the competition-it is time to take the help of demographic data, and what better serves the purpose than ‘Inferential Analytics’. 

Here are three tips on how you can boost the revenue of your organization by making the most of Inferential Statistics.

  1. Development Plans– Often business leaders plan to expand their company or open a branch at a new location, but how to derive information about the customer base, delivery system, distribution scheduling etc. ? 

With Inferential Analytics, you can get key insights on such aspects, coupled with business intelligence reports. Such information is extremely crucial for expansion plans, especially at a new location.

  1. Locate your audience– With the help of Inferential Analytics that examines your current customer data, it is possible to find out where people are most likely going to take benefit out of your product or service. Add to it, you can also narrow down the region where the possibility of customer potential and expansion is high.
  2. Create a marketing campaign– With the help of Inferential Analytics, a business leader can narrow down the branding requirements and focus on specific consumer preferences in a bid to stand out of other competitors in the region. Together with such data, it becomes easy to create a successful marketing campaign.

Grow your business with Inferential Analytics

Expansion of business is nothing less than a big challenge. Not only it takes time and dedication, but also careful location planning. Only with proper location segmentation that helps categorize targeted customers can a business reach its heights.

When the importance of location and population is so impeccable, Inferential Analytics importance cannot be ignored.

If you are blown away by the relevance of Inferential Analytics on business and wish to incorporate it into your company, team members of SPIN Strategy can be of great help.

 

It is a time in history when devices that rove around the globe is empowered with a plethora of multi-functional technologies that can capture gestures, show clear readings to proximity temperature, etc. the list just goes on.

Internet of things is to be held accountable for such versatility, in bits and pieces, but does that clearly throw light upon the importance of this technology? With the ‘Big Bang’ of data and connected devices (the key foundation of IoT), the business sector is all warmed up.

However, the point of discussion over here is that in the absence of understanding to interpret data, and comprehend which one should take a lower priority, IoT is nothing but an unstructured flow of ineffective data.

The absence of AI deployment in IoT enabled devices stands as a ball and chain towards the blistering development of technology that put a veil on the real prize of humankind the astonishing transformation prospects, which IoT offers.

In support of this argument, market survey reports state that more and more organizations have turned to AI to not only improve but also change their business operations.

AI boosts IoT enabled devices

If a company has picked up pace in recent years, it is quite obvious to say that the business organization has inculcated rightful amalgamation of AI and IoT. For instance, Uber uses AI to connect the right passenger with the driver, thanks to customer behavior recognition and autonomous driving approach of data science.

For a highly operated IoT device, in order to comprehend what’s really taking place around a device and to respond dynamically, AI is the key tool. For this, AI needs to be deployed in the right manner, in a bid to realize the IoT offered benefits.

Key Considerations for using AI in IoT

To incorporate AI and derive maximum value from the data IoT makes available, business needs to consider some key steps.

  1. Consider how to incorporate AI training into the process
  2. Ensure the AI systems are constantly refined and enhanced

To conclude with AI in IoT

AI training is as crucial as algorithmic coding for traditional systems, however, in the present scenario that is a worldwide challenge.

With the right training model, IoT models can balance a pragmatic approach toward devices that have human intervention and contribution at the forefront.

If your business has IoT enabled devices, it is quite likely that you will aim to upgrade it with AI, but only with the helping hand of a professional.

SPIN is that professional you seek. Contact today!