Make Your Marketing Campaigns More Effective With Big Data

Make Your Marketing Campaigns More Effective With Big Data

It will not be an exaggeration if we start by saying, “Big Data is shaping the future of all corporate operations.” From logistics to talent acquisition from performance evaluation to marketing campaigns, big data has been a driving force in decision-making in all corporate operations. However, the biggest impact big data has made is in the field of marketing and sales. Today, we look at some of the areas where the use of big data has helped marketeer improve the results of their marketing efforts. If you are a digital marketer or are just associated with any marketing campaigns in general, you too can sharpen up your marketing efforts using big data.

Offer Better Customer Experience

The modern consumers get hundreds if not thousands of marketing emails, SMS, and a plethora of other marketing content in their inboxes every day. How many of them actually capture the attention of the consumers? Almost none. Ok, some do manage to get a click or two, but with the digital marketing budget skyrocketing every day, do you think an online marketing campaign fetching a click or two is actually worth investing? We don’t think so.

This is where big data comes into the picture. Big data helps you to customize your marketing campaigns to target your potential customers in a highly engaging and personalized way. This not only makes the campaign relevant for the user but also makes the consumers feel special as they see only the relevant content featuring in the campaign.

Big data analytics allows you to understand the consumer behavior through the content they are accessing on your website, the device they are using to access the content or just the general content they are interested in. Based upon all those data points and understand the buying cycle of the consumers you can offer them the products and services they might be interested in. It boosts the chances of a potential customer actually becoming a customer a lot higher. You even can use the geographical locations of your consumers to offer them localized deals and offers. This approach of personalized marketing campaigns boosts your conversion rates, engagement with the customers and brand loyalty in general. So, use data to know your customers better than you already do.

Discover New Opportunities

Identifying and tapping the growth opportunities at the right time is the key to the success of any business. And with the help of big data and machine learning, you can identify any growth opportunity just in time to prepare your business for it. Using the data from your organization’s customer engagement platform with the publicly available data for the consumers your business analyst can help you identify new markets and opportunities for growth.

This field of data analytics uses predictive analytics to identify new targets and growth opportunities in the said markets. Using the predictive analytics you can evaluate the potential growth opportunity based on the market share you have in any particular region and the areas of improvement to boost those numbers.

Precise Attribution

The success of any marketing campaign can only be evaluated based upon the conversions it drove towards your business. Earlier, the marketers used the last-touch model to determine the marketing attribution. However, the issue with this approach is that it does not take into consideration the online and offline campaigns or activities that led up to the conversion. And this is where Big Data comes into play. Using big data, the marketing experts can precisely identify the events triggering the conversion and sales for all your marketing campaigns.

The marketing experts these days have strong attribution tools which enable incremental attribution through all your marketing channels like display, social media, email marketing, or the Google or Facebook ads. This makes it easier for the organization to allocate resources making all your marketing investment give the best ROI.

Final Thoughts

With the growing technology around us, the role of big data analytics in coming years is only supposed to go up in the coming years. So if you are looking to sharpen up your marketing decision making or just make your marketing campaigns even more effective, big data is the way forward. ')}

Let’s bring down that bounce rate

Let's bring down that bounce rate

Nothing hampers an online business more than a high bounce rate. It can also be attributed to the failure of a large number of e-commerce businesses on a regular basis. To understand it better, let’s simplify what a high bounce rate means. For the uninitiated in the field of digital marketing or Google analytics, a higher bounce rate for any website indicates the number of visitors leaving the website immediately or soon after visiting a website. Now, if it’s an e-commerce website, a visitor leaving the website means a potential customer walking out of the shop door, soon after entering the shop. It also means that they are not buying anything.

And when you consider the fact that the entire idea behind the existence of any e-commerce website is to make consumers shop online and sell stuff. It seems rather jarring.

If you are not able to make customers shop despite having a pretty looking website, an established brand name, and spending big on your digital marketing campaigns, you pretty much do not have an e-commerce store. ‘

However, to understand Bounce Rate for an e-commerce website, we first need to understand Bounce Rate in general. Technically, bounce rate for any website is the percentage of users who leave the website only after visiting one page or the home page. And for an e-commerce website, every customer leaving the website only after one page means an opportunity lost to sell something. Now, we understand that even after spending several pages and browsing several products a customer can decide not to buy anything and that is perfectly all right. There is nothing you can do over the internet to persuade any customer to buy every product he/she browses. However, there is something you can do to establish a relationship with the visitors, turning them into recurring visitors and eventually buying customers.

So, here we have listed some of the easy ways you can adapt to persuade even those finicky visitors to shop with you.

  • Focus On Your Product Pages

If we have to pick one page of the website that can turn a prospect into a customer, it will be the product landing page. You can have a jazzy homepage, a quirky welcome message to greet your customers, or even an attractive video to capture the attention of the visitor, but ultimately it’s the product landing page that will decide the fate of the visitor.

Your prospect will browse the specifications, the product reviews, the customer reviews and every single detail about the product on that page before deciding to put money down the table for it. Even the savviest of digital marketer will have no part to play in the decision that your prospect will be made after reaching the product page.

This is why it’s of utmost importance to optimize the product page to the best of your ability. Here are some tips to help you optimize your product page to boost your chances of converting a prospect to a customer.

  • Make the product page easily accessible. At any stage of browsing your website, the visitor should be able to reach the product page of his/her choice in as few clicks as possible. Ideally 3, you can even bring it down to 1.
  • Present all the product related information like reviews, specs, in a neat and well-segregated manner.
  • Highlight the “add to cart” button, so the prospect can add the product to cart as soon as he/she has made the choice.
  • Do not confuse the customers by showing too many “similar” products.

  • Divide your email list

We have discussed it in the past in some of our earlier blog posts and we will say it again, a personalized email marketing campaign will yield you a lot better results than a generic one. This is why the more you segment your email list, the better CTR (click-through rates) you will get for your email marketing campaigns.

Basically, email list segmentation is all about grouping your customer base based on their interaction with your website, ads, products, or just emails. You can even use the power of machine learning and big data, to further narrow down your prospects.

Using machine learning and big data you can even segment your prospects based on their likes, dislikes, their interaction with your offers and a lot more. Once you have a segmented email list with you, you can send them emails and offers that match their interests. These personal recommendations make the customers feel special and boost the chances of them shopping with you.

You can even personalize your website messaging, chat support, or even the SMS campaigns to boost the customer engagement on your website and consequently bringing down the bounce rate for your website.

  • Make shopping with you a seamless experience

Nothing hinders online shopping experience like a cumbersome checkout and product search functionality. This is why it is of utmost importance to offer a seamless shopping experience to the customers. Make sure you have your CTA (Call To Action) buttons, your products are easy to find, and all the information related to the product and its delivery is displayed in a proper way.

Lack of information related to product and terms of services should not be the reason why you lose your customers.

Having all the relevant information related to the product and terms of services boost the customer engagement and consequently brings down your bounce rate significantly.


It’s vital to build a relation even before you make your first sale and in the world of online shopping the only thing that can assure you a sale is the trust of your customers. If your customer doesn’t trust you, they are never going to buy from you.

This is why it’s very important, to be honest with your customers in terms of the information you provide them and offer them a pleasing experience on the website rather than shoving your products down their shopping carts right from the very first click.

So, make your website likable first, the bounce rate will automatically come down. ')}

A Primer On Big Data & Artificial Intelligence

A Primer On Big Data & Artificial Intelligence

Big Data and Artificial Intelligence are two buzzwords that keep making their appearance even in everyday conversation these days. Statements like “data is the new oil” and that “artificial intelligence is the future”abound in the tech circle.

From Facebook to Amazon and Google to Microsoft, every major tech giant is investing inordinately in big data and artificial intelligence.

In one of his statements back in 2016, Google’s CEO Sundar Pichai said,

The last 10 years have been about building a world that is mobile-first. In the next 10 years, we will shift to a world that is AI-first.

When you hear statements like that, you tend to take note of it. Now, despite of the buzz around big data and artificial intelligence, the difference between the two is rather murky for a major chunk. A lot of executives around the world still pit AI against Big Data, which although is a common mistake as the two go hand in hand, but they, in fact are two different tools.

Thus, it is critical to understand the difference between AI and Big Data.

AI & Big Data: Different Tools To Achieve The Same Task

Simply put, Big Data is the huge dump of unstructured data in the form of sounds, texts, images, transactions, messages, social networks, videos, etc. Artificial intelligence, on the other hand, is the science of computer programmes, which process that huge chunk of data and gives a structured pattern or output. This is the inherent difference between the two.

Breaking it down further, we can define artificial intelligence as a form of data computation, which gives a structured and detailed analysis of the data set fed to it. Some ways in which AI accomplishes the data analytics are:

  • Natural language processing (NLP): Understanding the human language and interpreting it accordingly.
  • Computer vision: Image processing using technologies like Tensor Flow to give computers the ability to identify, see, and recognize images just like humans.
  • Machine learning: Using statistical techniques to help computers ‘learn & process’ the data are given, instead of being programmed for an explicit function.

All of the aforementioned technologies allows the computer to execute cognitive functions like analyzing and reacting to the data set just the way humans do. One can argue that that is exactly what the traditional computer apps do too, and they will be right. Although, in case of traditional computers the reactions and responses from the computer are being hand-coded, which when you are dealing with big data is just not possible and in case of even the slightest of a curve like an unexpected entry, the traditional app fails. The AI systems, on the other hand, adapt to the change and accommodate the change in modifying the output. The purpose of AI is to evolve the computer functions up to the levels of human knowledge by giving them the ability to learn, reason, and then apply all of it for problem-solving.

Now the question is, how does all of it happen? And the answer to that lies in Big Data.

Big Data – The fuel for AI

Artificial Intelligence has been discussed at length since the ’90s. One fine example of it is its cinematic mention in the movie “The Matrix” in the year 1999. Humans combating with the machines that have developed their own intelligence, that’s AI for you in the nutshell. However, when it came to execution, AI was still a rather edging technology until in recent times.

The big bang in the world of artificial intelligence occurred with the dawn of huge parallel processors, to be very precise, the GPUs (Graphics Processing Unit). These GPUs are colossal processing units containing thousands of cores as opposed to the mere dozen in your traditional CPUs (Central Processing Unit). All those cores gave enough juice to the existing AI algorithms to carry out massive operations with absolute ease and made them viable.

These processors, when fed with the Big Data, allowed machine learning algorithms to assimilate and deduce a pattern or reproduce a behavior. It is worth mentioning that artificial intelligence, for all its intelligence, still can not deduce patterns and behaviors like we humans do. It acquires its intelligence through trial and error, and for that to happen successfully it entails big data.

One of the key reasons why AI apps of the past were not as effective or efficient as the ones we have now is due to the lack of data set. But now with a huge volume of data available with the organizations and faster processors, AI apps are thriving in every walk of life. The widespread access to the internet has also allowed for the real-time data to be fed to these processors for real-time processing and generating the output.

The self-learning ability of artificial intelligence enables them to extract the answers to all your questions from the data fed to it. It makes data an intellectual property and if you have the best data set in the world, even if everyone is using artificial intelligence, you will come on top. So, it will not be an exaggeration to say that, there will be no Artificial Intelligence without Big Data.

AI and Big Data Together

It’s safe to say that Artificial Intelligent (AI) needs big data to thrive. The better the data, the more effective your AI analysis will be as it can learn and evolve. Big data enables Artificial Intelligent (AI) to do wonders. So, you can say that there will be no artificial intelligence without big data.

From being deemed as a revolution to be called as a curse, AI and Big Data both have had their fair share of accolades and criticism. But whether you see them as technological developments that will change the future for mankind or a blossoming catastrophe, we will only find out in the future. ')}

AI and Hyper-Personalization

AI and Hyper-Personalization

For many, the age of personalization in the field of advertisement and marketing began when they first got the mail that was addressed as “Dear Marry” as opposed to an anonymous greeting like “Dear Sir”. To an extent they are right. Many of us in the world of advertisement and marketing woke up to the power of personalization with the significant success of personalized campaigns as opposed to the generic ones. Since then, consumers have been bombarded with hundreds of promotional messages on a daily basis.

As a result, the consumers have lost the interest and excitement that they once had for such personalized emails and campaigns. It has made it harder for the brands to engage with their consumers on a personal level. Marketers all over the world are working to find an effective solution to all of that and they might have found one in Artificial Intelligence. With the monumental rise of artificial intelligence and machine learning in recent years, their implementation in pretty much every field has been groundbreaking. So, why not marketing?

Now, as we all know, data is at the core of it all. To make an AI implementation work for you, you need big sets of data. The bigger the data set, the more relevant and useful information will we be able to extract. While this marks the beginning of a totally new marketing approach – Hyper-Personalization, it is the end of the road for the segmentation approach. And from the looks of it, hyper-personalization is the way forward.

So, let’s take a closer look at the Artificial Intelligence-Based Hyper-Personalization and how it changes the conventional marketing techniques we’ve all grown up on.

The emergence of big data

Data is the new oil” we all have come across statements like this more often than we care to count. Mostly in recent times. This significant rise of big data and companies capitalizing on it is the biggest factor behind the meteoric influence of technologies like machine learning and artificial intelligence in every field. The machine learning algorithms, when running through a huge set of data sets, can draw patterns and conclusions in minutes, for which the human brain will need years. It computes consumer behaviors such as their likes, dislikes, their shopping pattern etc making it easier for the marketers to target the consumers.

The feedback loop

One important part of hyper-personalizing the online marketing campaigns is constantly tweaking the consumer details after every campaign. This is done through a feedback look, which is a part of Artificial Intelligences’  self-learning. In simple terms, a feedback look is a simple process which constantly gives feedback on the decisions made by the system. Based on the feedback the AI system learns whether the decisions made were right or not and if they need any tweaking. Depending on the outcome the algorithm is smart enough to tweak itself according to the new data to help marketing teams.

Understanding the difference between Personalization and Hyper-Personalization and

It’s easy to confuse personalization with hyper-personalization if you are just starting in the world of AI. However, they both are totally different. While personalization deals with the personal and transactional data like name, purchase history, and basic profile details, the hyper-personalization is all about the behavioral data in real time.

To help you understand hyper-personalization better, let’s take the example of an online shopping website. You sign up with them, you search for products there, you spend hours finding the right product and then you finally place the order. Now all of those actions you took becomes the data point for that particular website. Now they know your name, search query, your purchase history, and brand affinity etc, an average spend amount, etc. They can use all that information to create a profile for you for a very personalized email, which will only feature things that you like.

Why Hyper-Personalization?

Studies have found the hyper-personalized campaigns to be almost twice as successful as the general campaigns. In fact, in the world of e-Commerce, it amounts for the 60% higher conversion rates as opposed to the normal campaigns.

The best thing is that hyper-personalization not only helps the brands, but it incentivizes the brands as well. The consumers are now able to find deals and products at better prices and just in time of need. They get the promotional campaigns for the products that interest them as opposed to a whole gamut of products that might not be relevant to them. It’s a win-win for all.

Finally, with artificial intelligence being the driving force behind the e-commerce world, technologies like hyper-personalization are bound to make marketing a lot effective. So, if you are looking to leverage the power of artificial intelligence for your business, listing it on product discovery platform like Taglr, is a smart step forward. ')}

Big Data – What It Can Do For Your Business

Big Data - What It Can Do For Your Business

Big Data is the easiest way to understand the modern world. As technology penetrate our lives, the influence that data can have on anything and everything we do is unmeasurable. Both offline and online. Almost anything you do turns into data for the technology.

As a consequence, we’re inundated with virtually endless facts, perceptions, numbers, and percentages in our hand. And, understanding and studying this overwhelming amount of information on hand is what Big Data is all about. A little complicated, but of great use.

A Closer Look At Big Data –

The information scattered across in form of traditional or digital form is huge. Bringing all that information under one roof for a specific purpose could lead to a greater understanding of the modern world. It could be used as a constant source of discovering new patterns and analysis. Tech companies use this large amount of data to analyze consumer behaviours, market trends and tailor their services or products accordingly.

One industry that has specifically leveraged the power of Big Data to a greater effect is the world of e-commerce business. All big e-commerce businesses in the current market use big data to understand the market trends, customer behaviour, their buying patterns to streamline their operations and gain more customers.

So, it’s about time we look at how big data is transforming the e-commerce market and how online advertising and product discovery platforms like Taglr is helping smaller retailers harness the power of big data.

In-Depth Shopper Analysis –

For any business, it’s of utmost importance to understand their shoppers behaviour. Big Data makes it easier for them. By analyzing big chunks of data and preparing analytics on latest trends, customer preferences, and the growing demands, business owners can now make sure that their products are in store and are being promoted accordingly. Big Data analyzes all the searches made by customers to update you on any product that you don’t have in store or online but should have. Big Data analysis continues to illuminate the changing customer behaviours like the most popular shopping time, the most popular products, and many such things to help you seize new business opportunities.

In the modern competitive market, more and more offline retailers and online stores alike are using Big Data analytics to tune their marketing strategies, inherent shopping processes, and social media advertising to boost their sales and customer engagement.

Improved Customer Service –

In the modern competitive market, one bad customer service experience can cost you a customer, forever. According to a study, a major chunk of customers will not shop from a business with which they have had a bad customer service experience in the past. A good customer service is a key to success for all modern businesses, online or offline.

Taglr’s Big Data analytics provides predictive monitoring on the issues your customers are/will be facing, to streamline your customer service and make sure that the problems are resolved at a faster pace.

Easier and Safer Online Payments –

Big data has the capability to integrate multiple payment gateways on one platform. It not only makes it easier for the customers to use but also minimises the online fraud risks. The advanced data analytics is strong enough to identify payment frauds in real time and raise a concern immediately.

Furthermore, big data can also identify money laundering transactions, which might appear as legitimate transactions to naked eyes. With all the safety combined with ease of use, data analytics makes it easier for the online and offline businesses to sell and upsell.

Seamless Integration With Mobile –

The number of smartphone users is constantly on the rise. According to a recent study, we might be already approaching towards the time where desktop computers will become obsolete.

And in such times, big data fits right in. Businesses can now collect more native data to transform their products and services. They also can gather data from different sources to analyze their potential customers at once.

We already are seeing Google giving preference to websites that are mobile friendly and responsive. So, in case you do not have a mobile-friendly website, fret not, you can still open your store with absolute ease on Taglr to reach the right customers.

Final Thoughts –

The increasing adaptation of Big Data by e-commerce industry could very well be the difference between a successful store and a store longing for customers. Whether you are looking to take your business online or just want to advertise your products online, online product discovery platforms like Taglr can make it happen for you with absolute ease. Taglr offers a wealth of technological tools like in-depth analytics using big data, machine learning, and artificial intelligence to help you find success in this modern technology-driven market. ')}

Research Online, Purchase Offline Is The Way Modern Shoppers Shop

Research Online, Purchase Offline
According to a study, almost 65% of modern shoppers prefer to do a little to extensive product research online before stepping foot in any store.

The pre-purchase behaviour of modern customers plays a decisive role in their shopping decisions. Consumers today are empowered by many tools that enable them to do an extensive research online before putting money on the table for the purchase. This move from clicks to bricks with absolute ease, calls for effective measures to be taken by the modern retailers to understand their customers and enable them to browse and buy to maximize the profit margins. However, it is a lot easier said than done. While the customers have the freedom to browse and buy from any store, online or offline, of their choice, the retailers struggle to tap into these shoppers due to the sheer unpredictability of their move.

This is where making use of technologies like Big Data analytics, Machine Learning, and a bit of Artificial Intelligence can give an edge to the retailers. To tap into the right consumers it’s very important to identify where the journey of the shopper actually begins. And the retailers that harness the power of aforementioned technologies together with engaging digital content, findability based on the geographical location, keywords, and SEO (Search Engine Optimization), are bound to win the game.

And with Taglr, we are trying to put our retail partners at the forefront of it all. So, let’s have a closer look at the latest trend that is – Research Online, Purchase Offline.

Understanding research online, purchase offline or ROPO –

The increasing penetration of internet with increasing number of smartphone users is converting the modern consumer into a research obsessed buyer. An integral part of any modern purchase is the initial research that goes into shaping up the final purchase decision. Whether the consumer is in the store or in the product aisle itself, the convenience of researching products online prior to putting them into the cart plays a significant part in determining what ends on the billing counter and what remains on the shelf.

According to the latest study, almost 67% of the customers admitted to researching products – occasionally – if not regularly before walking into a brick-and-mortar store for the final purchase. Some more admitted to having a pre-shopping routine, which included extensive online research among many things. A very small number, almost 33%, admitted to not making online research a part of their shopping journey.

All of this data highlights the fact that whether you are a multi-brand retailer or a fashion brand or a retailer with omnichannel presence, you need to have a firm grip on the digital channels to ensure that you are present where your customers are seeking you.

Understanding The Shoppers –

When we talk about research-obsessed shoppers, a millennial with a big smartphone roaming around the store is the first image that comes to our minds. Doesn’t it? However, we could not be far from reality. According to a study, the younger shopper base aged between 18-24 years aren’t as obsessed as their older counterparts. As per the study, almost 54% of shoppers between the age of 18 to 24 years said, they do not do an extensive research on products online before visiting the store. However, a lot of it could be attributed to factors like impulse shopping and the fact that most of their shopping includes low-risk items.

On the other hand for the older shoppers between the age group of 24 to 34 years almost 73% research online – occasionally if not every time – before stepping into the store. And while a lot of it can be attributed to the responsible behaviour of these shoppers, it’s very important to understand that these shoppers account for the most sale in the modern market. They not only like to read reviews of the products they intend to buy but also like to know all the key facts about the items they are about to buy.

The same is applicable to the shopper above the age group of 34 years. The mature the shopper, the larger is the extent of research that goes into any shopping. This is what makes having a strong digital presence and a thorough understanding of consumer behaviour such a decisive factor in the modern market.

So now, let’s see how to capture these research obsessed shoppers for your business

The key to success in the modern research obsessed market is to have impeccable digital capabilities. The content to go with it will give you an added advantage. Let’s have a look at both these things one by one.

The technology has grown leaps and bound since the time you last visited the supermarket so it will be unfair to overlook it in aiding your business. The increasing use of Big Data to understand customer behaviour, buying patterns, the best time to sell, and pretty much any metric that can be used to boost the business and capture the shoppers at the right instance is changing the modern retail market. And we at Taglr are trying to do just that. The expansive use of technologies like Big Data, Machine Learning, and Artificial Intelligence to predict, study and understand the shopping behaviour makes it easier for us to provide smart analytics to our retail partners to empower them to tailor their offers and deals for maximum profits. Taglr is a unique product discovery platform for modern retailers which enables them to harness the power of modern technologies to capture the research obsessed customers.

Now, as far as the content goes, Taglr uses advanced machine learning algorithms to generate a wide array of keywords to match with the relevant products to make sure that the customers find what they are looking for with absolute ease. We also encourage retailers to have deeper understanding of rich content to go with their products to make sure that their products are easily discoverable by the consumers. Pieces of information like product descriptions, photos, specifications,  and reviews play a significant role in the Search Engine Optimization of the product page and make them easily discoverable, making it a priority for every retailer in the modern retail market.

In the end, while we agree that it’s difficult to predict where the shopper will begin his/her journey, but what is easy is to predict the fact that the research will always begin online, and if your brand/store is not discoverable there, then you clearly are missing on a major chunk of market pie. ')}