Despite what some may believe, SMBs (small and medium-sized businesses) are not simply smaller versions of enterprise organizations. The size of a company has a deep impact on how a company is organized, but most importantly, it impacts the purchase processes. Since we are talking about different sales processes, we also need to define a different forecasting approach for each type of company. In the following post, we will go through the most important factors that dictate the differences between enterprise and SMB forecasts.

The sales cycle

The complexity of the sales cycle is the main factor that affects the differences between enterprise and SMB sales forecasts. For starters, enterprise sales have more complex sales processes and longer sales cycles. This happens because the decision-making process is often divided between several stakeholders, not to mention the fact that decision-makers are harder to reach in an enterprise. Moreover, each enterprise can have its own purchase process, which can be more or less complex, affecting the length of a sales cycle. On average, an enterprise purchase decision requires the consensus of 7 stakeholders. The longer a sales cycle is, the harder it is to predict its outcome. SMBs have shorter cycles because their needs are more urgent, and their purchase processes are less complex. On the other hand, with enterprises, a cycle can take more than 6 months, so it will be harder to make quarterly forecasts for these companies.

The accuracy of historical data

Historical data is the heart of a forecast, but the accuracy of this indicator can vary based on the size of the company in question. The reason for this is very simple: smaller companies tend to have shorter and less complex sales cycles, which leads to more concise and more accurate historical data. Enterprises, on the other hand, have complex sales cycles which can be affected by numerous variables such as the availability of decision makers, internal purchase processes or last-minute budget cuts. Due to the complexity and volatility of enterprise sales, enterprise forecasts need to be more complex and include as many variables as possible to increase the accuracy of their historical data.

The sales reps

As the sales processes differ for enterprises and SMBs, so do the skills and the goals of the sales reps. Enterprise sales representatives are often more analytical as they use more market date to state their points and stay ahead of the competition. Moreover, enterprise reps are also farming sellers, which means that their end goal is not just to make a sale, but also to get as much business as possible out of a new or existing client. SMB reps, on the other hand, are more aggressive, they deal with less competition, but they also have less experience and less data to make informed predictions. Since there are several forecasting methods which consider the predictions of the sales reps, it makes sense that the different skills of the sales rep will impact the final predictions.

Another way in which sales reps can impact forecasts is by abandoning leads in the middle of a sales cycle. This has a bigger impact on enterprise sales which can take months to finalize. Having an enterprise sales rep leave in a middle of a deal will not only impact the morale of the whole team, but that rep will take with him all the business relationships that he nurtured, relationships which will have to be rebuilt from scratch.

The complexity of the deals

Enterprise sales are far more complex than SMB sales. When selling to SMBs, you could close a deal from the first contact with a new lead, but this would never happen with an enterprise client. The more people there are in a company, the more complex the deal will be. Enterprise sales also leave more room for upselling or cross-selling, not to mention the fact that most enterprises prefer customized products.
Conclusion: As you can see, enterprise and SMB sales deal vary greatly. The differences in the sales processes require a different set of indicators which will affect your options in terms of forecasting strategies. To know which metrics, you need to track and to increase the accuracy of your forecasts, it is essential to understand the needs of your clients and the complexity of your deals.

Inventory issues are a business owner’s worst nightmare.
Especially when you’re in a growth phase, and in the middle of expanding to meet customer demand, it can set back your sales team and impact your bottom line.
Whether you’re an e-commerce or brick-and-mortar store, inventory can get the best of you, and when it comes to inventory forecasting, the majority of retail business owners simply don’t know where to start. Failing to have a sales and inventory sales forecasting plan will usually lead to lost sales, time wasted running around in circles.
What’s the solution? Inventory forecasting.
Inventory forecasting assists businesses in optimizing their inventory purchasing what products to buy, how much to buy, and when to buy. Alternatively, it assists in knowing when it’s time to liquidate unsold inventory.
The key with inventory is understanding past trends to the past to predict the future sales potential. When a business is operating on a “what’s to come” basis rather than just focusing on what’s happening now, operations can run smoothly, especially with inventory.
Here are five reasons why inventory forecasting is essential for the success of your business:

  1. Better cash flow

Let’s face it. We’ve all been there. Cashflow is tight because we just made a huge inventory purchase. Then for the next few months, we begin to get anxious as to why it’s not moving fast enough. When you optimize your business with inventory forecasting, you can accurately predict how much inventory to buy every time so you’re not put in a tight spot with cash flow for your business. And in today’s rapidly changing sales landscape, that makes all the difference.

  1. More time

It is not easy running an entire business. Most days, there are several fires to put out at once, locations to run, customers to keep, suppliers to manage and employees to maintain. You’re busy enough trying to deal with daily operations. Investing time in sales foresight is yet another issue on your mile-long list that is eating away at your time. Forecasting involves various preventative measures so you don’t have to spend hours constantly putting out inventory fires. By making it a part of your business operation, you’re ensuring that you will have enough time to run your business actively, instead of reactively.

  1. Simplify operations

With proper forecasting strategies and procedures, you can cut out a lot of complications and processes that are slowing down operations. Inventory forecasting allows simplicity to take over so you can operate on a step-by-step plan instead of jumping all over the place in your inventory tracking.

  1. Save on labor with software

With the ever-increasing technology, businesses are able to cut back on unnecessary labor costs. If an algorithm can do it in way that’s quicker and unbiased, then why hire an employee? Inventory forecasting software is able to complete the simplest tasks to even the extremely sophisticated. One of the more sophisticated tasks, for instance, is predicting what products a customer is likely to buy if they buy a specific one. (eg. if a customer buys product A there is a 93% chance they will also buy product B).

  1. Increased sales

If you’re wanting to ramp up your business to the next level, then it’s time to pick up that money left on the table. Without proper inventory forecasting, your business is losing money. According to a study done by IHL group, retailers lost $1.71 trillion due to out-of-stocks in just one year. This is easy money lost due to lack of forecasting. By preventing out-of-stocks you can prevent a big chunk of lost revenue, and cushion your annual revenue.
As you can see, implementing an inventory forecasting strategy is crucial in ensuring the success and future growth of your business.. Especially when you are in a transition and need to consider whether to hire more people or make that big inventory purchase, inventory forecasting is an essential tactic to lower risk and increase performance in your decision making. 2019 could be the year you save you hundreds of hours of mindless number crunching and even thousands in profit by simply implementing an inventory-forecasting plan.
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Running out of stock is one of the last things that any retail business owner wants when a product is in hot demand. It is not only disappointing, but it leaves money on the table by letting your customers search for alternatives from your competitors. To avoid such a scenario, inventory forecasting needs to be utilized and implemented across all retail businesses, from mid-sized operations to large-scale enterprise companies.
Inventory forecasting isn’t simply a matter of analyzing past historical trends and predicting future demands. Accurate inventory forecasting requires the right data set from multiple data sources.
Before diving into the data and stats surrounding demand forecasting, it’s worth noting that, within the supply chain context in the eCommerce industry, there are three main types of forecasting, which are:
Demand forecasting:  This is the investigation of the companies demand for an item or SKU, to include current and projected demand by industry and product end use.
Supply forecasting: Is a collection of data about the current producers and suppliers, as well as technological and political trends that might affect supply.
Price forecasting: This is based on information gathered and analyzed about demand and supply. Provides a prediction of short- and long-term prices and the underlying reasons for those trends.


90% of Retailers Fail in Forecasting Since they Ignore Lost Sales

A recent study carried for 2018-2019 period by Neogrid points out an important aspect that many retailers ignore when making their forecasts. The report says that 90% of small businesses do not use their past lost sales to make future predictions. Most of them only focus on demands which sometimes changes hence resulting in huge losses.

With a report of past losses otherwise called historical lost sales, the prediction will most likely be reliable. If you, therefore, run a retail business and would like to make accurate predictions, then make sure you have figures of your historical losses. Use them together with stats on demand, and your inventory forecasting won’t fail.

Retail Businesses Face Serious Problems Even After Spending a Lot on Inventory Management

Reliable information from Bossa Nova, a leading provider of data service says that one of its surveys found that even despite the huge spending that retail businesses make, 73% of them still make inaccurate forecasts. It further reports that most of the problems encountered are as a result of price inaccuracy among others. It, therefore, means as a retail businesses owner, you need to take the time to get accurate prices if you want to make accurate inventory forecasts.

Automating Your Retail Operations Boosts Productivity and Accuracy

Bossa Nova survey report indicates automation could be all you need to improve your productivity. In fact, 73% of the retail businesses interviewed reported that their employee productivity improved when they introduced robots. Furthermore, the same study says that 74% of the retail business owners interviewed expressed their confidence in automation. They argue that their accuracy in inventory forecasts increased when they automated their operations. You should, thus, consider automating operations as well as predictions if you want to improve accuracy, and most importantly, the productivity of your employees.

67% of Retail Businesses Think that Inventory Analyses and Forecasting is a Waste of Time

While inventory analyses and forecasting is being promoted as one of the strategies of making reliable predictions about the future, some retail businesses see it as a waste of time. In fact, 67% of businesses interviewed in Bossa Nova survey released on 28th Feb 2019 feel that spending time analyzing inventory isn’t a good way to use employee’s time.
Instead of spending time on inventory forecasting, most retail businesses often focus on serving the customers present at a given time forgetting that the future is also important. While such an approach can help maximize profits, it is important to note that demand changes with time. A business can only rest assured of existence in the future if it plans ahead through inventory forecasting.

Most Retail Business Lag Behind Technologically

Over 80% of retail businesses lag behind when it comes to the use of technology to find solutions to problems. What is happening is that technology is rapidly changing, and there are so many new technologies that retail businesses can utilize these days. Are you among those lagging behind? Your retail business can make great strides with the right technologies.
In conclusion, it is crucial for retail businesses to plan for future sales, and how to meet the demands of their customers without running out of stock. Alternatively, having excess supply will also mean losses and failed planning.


Curve uses machine-learning based prediction technology, allowing companies to accurately forecast sales, products, and support requests, to increase revenue and optimize profitability. Our unique technology goes beyond traditional business intelligence, by recommending the right solutions based on use cases and customer segments.

According to a report published by eMarketer in 2016, the trade and commerce sector will experience double-digit growth until 2020. During this period sales are expected to increase by over $4 trillion.
It’s clear that only a handful of industries can boast about such a beaming future. To make sense of our rapidly changing industry, we’ve compiled for you some of the most disruptive and potentially beneficial trends in e-commerce that marketers and consumers can expect to see in the very near future.
Greater Integration of Machine Learning and AI
Given the increase in marketing and business automation, it is inevitable that the commercial sector will continue to be influenced by a deeper level of artificial intelligence and machine learning in the years ahead.
In fact, machine learning is already integrated into today’s leading e-commerce retailers. In the upcoming years, however, additional e-commerce retailers will increasingly utilize the many benefits that machine learning offers in order to maintain their competitive edge.

Additionally, product recommendations, upsells, product bundles, as well as inventory forecasts, are also poised to become even more accurate and helpful. As a move away from keyword and human-based recommendations occur, merchants with a wider range of signals for product purchases history will become evident. In essence, retailers will have the power to know what the customer wants, before the customer does.


Voice search
It’s becoming increasingly difficult to talk about retail search without mentioning the advent of voice search. In the near future voice will be one of the leading drivers of online sales innovation, specifically with consumers on the go.

With an increase in the adoption of smart home appliances such as amazons echo and Googles Home, retail purchases are witnessing the incorporation of voice search,
Voice search, particularly in the smart speaker market, is not just a matter for convenience and neatness anymore, but it is the next stage for customer loyalty. For instance, the sales completed via Amazon Echo units also provided retailers with many new selling opportunities, with upsell rates of more than 60% for some product lines.
Faster shipping and better delivery logistics
One of the very few remaining differentiators when it comes to e-commerce sectors is the time and quality of delivery logistics that a retailer carries out. As we all know, Amazon is the indisputable king of e-commerce delivery and seems to remain firm on its throne for the coming future. Even more intriguing is the data on Amazon’s fastest deliveries- just eight minutes for a forehead thermometer and a mere nine minutes for 5 pints of ice cream.
We’re not too far away from a time when we can expect Amazon and other e-commerce retailers to step up their logistics game and offer their customers lower delivery times and better services.
Unprecedented growth in mobile checkout systems and IoT
These days, without mentioning the use of mobile checkouts and payment systems, anticipated e-commerce trends would not be complete. Mobile payment has been one of the most brilliant changes to the way people shop since e-commerce has skyrocketed. The mobile payment market has increased steadily since 2015, and now there are ten different systems available today. These also include Apple pay and Google pay as well as proprietary offerings from different banks including Chase and Softbank.
With ongoing innovations and new technologies being introduced daily, the e-commerce sector has and will continue to witness one of the fastest evolutionary shifts that the industry has ever seen.

In the last decade, artificial intelligence has made huge advancements and has integrated into almost every field, especially businesses and marketing. One of the major uses of AI and machine learning is sales forecasting. With the ability to process so much information at an incredibly rapid pace, it has become extremely beneficial for companies to turn towards the AI rather than traditional sales forecasting simulations.


Most people get confused between artificial intelligence and machine learning, as they may carry out similar tasks, however, there’s a clear difference between these two technologies, and we’ll help break it down for you.
First, it’s safe to say that the terms “Artificial Intelligence” and “Machine Learning” are often used interchangeably because both describe the use of software and hardware that enable a machine to be “intelligent.” However, the difference is that “Artificial Intelligence” is a broader term for providing machines with the ability to perform rational tasks, while “Machine Learning” is a subset of AI that encompasses the use of data for the machine to learn.


In general, AI is a concept where it is possible for a machine to “think” or react like humans. AI, Neural Networks, can learn by examples to execute arbitrary tasks. For instance, an AI ‘CRM’ solution can learn to respond to emails like humans. In essence, they can generate by teaching examples and very complex rules that humans follow.
Some people believe that just by stacking deeper and deeper artificial neural network, we will get a self-aware AI, and they call that hypothetical event ‘The Singularity’. However, that is highly doubted by industry professionals.

Machine learning is a bit more specific, as its main purpose is to read and learn the statistics and algorithms and learn from the historical data. In a nutshell, Machine Learning is taught to recognize patterns and make decisions based on statistical information. 


While machine learning is taught to gather data and learn it AI is mainly focused on applying the data. AI’s main purpose is to increase the successes it has in any objective rather than machine learning, which aims to increases the accuracy. In essence, AI aims to stimulate natural intelligence in the computers however the goal for machine learning is to maximize the performance of the machine by learning new things from the data. 
Sales forecasting that uses machine learning techniques, however, draws data from all historical sales forecasts and creates a model that shows a typical path for a successful sale, from start to close, and then compares it to current performance. Anomalies and an off-track forecast can be quickly detected in the data, which gives sales leaders the opportunity to step in and redirect ecommerce sales.
Utilizing Machine Learning technology such as Curve helps your team make more accurate sales and inventory decisions. All of these enhanced activities improve overall sales effectiveness and drive growth in an organization. At Curve, our mission is to help sales teams improve your sales outlook and drive growth across the organization.

There is nothing worse for an online business than running out of stock or alternatively being stuck with unsold inventory. Both of these scenarios will potentially impact your bottom line.
Regardless of how great your marketing plan is, or how well your eCommerce website may be converting, if you fail to plan ahead, your customer will find an alternative, no question about it.
Sales and inventory forecasting delivers the insights to easily identify obsolete stock in order to promptly liquidate it – thus lowering directly lowering the costs associated with keeping it on your shelves.
For these reasons and so many others, sales and inventory forecasting are extremely important, and the fact is that it really isn’t as complicated as some may assume. Using a combination of sales history and future trends in sales, Curve’s machine-leading based sale prediction solution can supply today’s top retailers with future sales forecasts, based on a variety of point for every product.
An important benefit to leveraging Machine Learning for sales forecasting accuracy is the ability of Machine Learning to ingest data and present that information at a granular level. Today’s leading retailers and marketers are using machine learning to understand, anticipate and act on their sales faster and with more clarity than their competitors.


Sales forecasting is for everyone anyone who has a stake in a retail or eCommerce business and takes interest in predicting its future sales. At Curve, we assist eCommerce and brick-and-mortar merchants make informed business decisions, using our machine learning sales forecasting technology.



  • Optimal Stock – Avoid being out of stock or having too much stock.
  • Advanced Analytics  – Get weekly, monthly and quarterly sales forecasts.
  • Sales Predictions – Totals per category or per individual SKU.
  • Location-based Data –  Forecast your sales by stores or sales channel.
  • Cut time and Cost – Automate time-consuming sales prediction tasks.

To Recap, best practice demand forecasting helps a business succeed in having the right product in the right place, at the right time. Curve helps you forecast sales by time frames and variables such as geographic locations, individual SKUs and much more. Sales forecasting is an essential business technique that delivers a visual representation of where your business is heading. It’s not just a fancy top-level solution, but can be used by everyone who has a stake in the business. If you haven’t done so yet, schedule a free demo with Curve today. 

As an online retail business owner, there’s certainly no lack of amazing e-commerce platforms available to choose from. So the question remains; How do you choose the right platform for your business? Some may have a bit of experience on the technical side and would prefer to have full control over every feature, while others may not have the necessary skill and would like everything laid out in front of them, plain and simple. We’ve put together a quick overview of today’s top e-commerce platform, to give you a bird’s eye view and help you make sense of the best fit for your business.


When trying to choose the right platform for your business, of course, you want the best. However, the best for someone else might not be the best for you. BigCommerce may be slightly more on the pricer side coming in at $29.95 dollars a month. The main question although is why would you pick Big Commerce for your business? The answer is its staff accounts. It may not seem like a big deal but if your business had five employees that need access to the account Shopify’s two won’t cut it. It also has clear directions on how to set up your business with 24/7 live chat support and if you’re starting that can be a blessing.


WooCommerce is generally a tier up from the novice at a business it is a bit more advanced. While it is not the most beginners friendly, it offers a lot more features. It is a Word Press website, and you will have to buy a domain name. It does get a bit technical but allows you to completely customize everything about your website and make it your own. It even comes off the top with its SEO. The best part, however, is that it is completely free with no extra transactions. It does not, however, compare with big commerce over features but what you get for the price is worth it.


Magento was one of the first e-Commerce websites on the market and has dominated it since then till 2014 when Shopify’s surpassed it in terms of popularity. Magneto is mostly free, but they do have a paid version for a large e-commerce business which does get expensive but offers a large number of advantages. It has a lot of users on it who will help you out for a small fee or even give you some free advice for free to help your site up. It has been used by many large brands like Nike, and gamble.


Shopify has built a huge fan base for itself beating out magneto in the popularity, coming out on top and maintaining that crown as of 2019. It has a quick and easy setup process with a dashboard for adding products easily. When you sign up to Shopify, it even allows you to import your products from any other platform you were previously using. Everything on their website is easily accessible, and their goal is to allow anyone to launch their business without needing development or design skills. It has 24/7 live chat support as well as unlimited storage, product orders, etc. It offers great flexibility, and you will be to launch any business.
While it can be a difficult and grueling process to choose the right platform, it’s always best to pick one that you are most comfortable with, and that can handle your needs. You don’t need to pay for features you don’t use so it’s better to start small and upgrade as your business grows.

We hear about it a lot, “The reign of brick and mortar retail stores is ending.” Today, the e-Commerce industry is the crowning glory, ruling the global market unlike ever before.
To put it in numbers, the four-year bankruptcy count now sits at 57 of once considered landmark retail chains. Manufacturing market share and in-store sales for consumer packaged goods are flat or declining. Online “microbrands” have devoured the lion’s share of growth, as e-Commerce’s gains continue to trounce retail as a whole.

With the online retail industry growing at such a rapid pace, merchants all around the world are actively working towards standing out from the rest. The truth of the matter is, if you want to be recognized, you need to step up your game, and here’s how.
Customers are putting in their money, and they do not want to take risks. If your website feels ‘un-secure’, then chances are your visitors will leave just as quickly as they landed on your site. Get a safety certification, and display your safety badge. Additionally, include contact details. A physical address can work wonders as well. This way, customers know that should there be any mishap, they can reach out to you.
Reviews are another great way to gain the trust of customers. If someone loves your product or service and tells others about it, you’re instantly building trust, as well as word of mouth marketing. This is social proof at its best. Humans tend to follow the herd, and they believe what the larger group says.
We’ve touched on this in a previous post titled Ten Quick And Effective E-commerce Sales Optimization Tactics, however, we can’t stress this enough. You know what they say – a picture says a thousand words (videos, more so). Go ahead and make your website eye-catching with great images and videos, but make sure they are relevant. We live in the age of visual culture. Images are everywhere. Which is why social media platforms like Facebook and Instagram are flying. Research suggests that websites or articles with images, get 94% more total views, as opposed to the ones that do not have images. So go ahead and deck up your website with some great images or videos of your product or service. However, the quality of the images and videos is important as well. Nearly 67% of online shoppers believe or trust images that are of good quality. Invest in a good photo op, and watch your sales fly.
Sure, we’re talking about e-Commerce but that doesn’t mean you shouldn’t be available for your customers. All customers love to be taken care of, so you have to be there for them if you want to succeed. So how do you do this? Enhance the customer experience by offering Live Chat Support. This way, you can address customer grievances as and when necessary. Also, try and be available on call at all times. To make your life a little easier, you could add a section that answers a few FAQs as well. Do a survey to figure out what the most commonly asked questions and issues are. This way, the customers can just skim through the list and solve their problems.
Over 55% online customers, that is more than half, abandon their shopping carts the minute they know that shipping charges are included. Everyone loves free stuff, and somehow, the customer mind set these days is that shipping should be free. Bearing the shipping costs might seem to be weighing heavy on your pockets but the rise in sales will eventually help you out. However, while this can be applied to several retail goods, there are a few that you cannot practically apply it to. Weigh out your options and see what works best for your business.
How many times have you visited a website, and left due to slow loading speeds? No one has time for a slow loading website! Two seconds. That is how much time 47% of online customers give a website to load. You or I do not have time or patience, in a world that is so fast-moving. Invest in a good website developer to make sure that your online portal is quick to load. Optimize your images, reduce the number of plugins, reduce redirects, minimize HTTP requests, enable compression, and reduce the server response time to ensure fast loading.

First impressions have been known to be the lasting impression. Now that’s an old adage that has been passed on for generations. Times have changed, but this saying holds true, even in an era where technology plays king. That being said, the question remains, how do you know exactly what makes the best first impression? Or in terms of eCommerce sales, what’s most effective for your business? That’s where A/B testing comes in.
A/B testing is primarily administered to see if your website is a hot favorite among customers. Simply put, It’s a method of determining which design, content or functionality is more successful with your site visitors. It allows you to test a variation of your page (or element on a page) that may affect your consumer’s behavior.
In most cases two websites are compared, to see which user interface works best for customer satisfaction, which in turn boosts your sales.
For example, A/B testing of your eCommerce site can involve:

  • Testing two alternative content layouts for the same product to see which layout produces more sales.
  • Various versions of product descriptions for your site to see which one makes it easiest for customers to find and purchase from you.
  • Changing the navigation menu or naming to see which results in more sales.

Find Out More About Curve’s Machine Learning Sales Prediction

Here are a few more great e-Commerce A/B testing ideas that all savvy and growth-minded e-retailer should try.

  • Split test your homepage: The inclusion of trust badges have been known to make a massive difference in a customer’s purchasing behavior. It’s a good idea to test out when and where your trust badges are shown.
  • Test your product pages: Creating a sense of urgency with flash sales at specific times can also create a surge of new customers. Try creating flash sales at different times to test what works best. It doesn’t have to be lower pricing, flash sales could include limited products, free shipping until X o’clock, buy one get one free, etc…
  • Test your checkout funnel: Add familiar trust seals, security promises, a money-back guarantee, eliminate steps, 1-page checkout versus 2-page checkout (or 3-page checkout), the order of checkout, requiring registration, and the details you ask for.
  • Test your category pages, your search results, and your thank-you page.

So far we’ve looked at a few split testing ideas that are sure to spark up your creativity, but it’s important to mention that you shouldn’t just change for the sake of change. You don’t test for the sake of testing. If you’re going to split test various phases of your eCommerce flow, you’ll want to have a data-backed hypothesis beforehand.

The basic steps for a successful split test include:

  1. Analyze your existing site: Identify hat you want to test. Set a benchmark
  2. Set a goal for it. You might want to increase the conversion rates, or decrease cart abandonment, or increase sign-ups, or lower the bounce rate.
  3. Define a process of how you want to reach that goal. For example, you might increase sales if the product page includes a video review, or shorten the checkout process.
  4. Create a variation to test your hypothesis.
  5. Run the test for an adequate length of time.
  6. Analyze the two sets of data.
  7. Implement the variation if it does better.

Ultimately, you don’t want to always be testing every little site change as it may leave you more confused, but a few choice tests can deliver big results.
When all is said and done, big results are the name of the game. Small consistent changes can create big profit, big growth, and big improvements.

If there’s one thing we’ve learned in the past year it’s that customer demands are constantly changing. Online shopping has become more accessible than ever, customer expectations are increasing, which means that online merchants need to be smarter about the industry. So we thought now would be a perfect time to share a few global eCommerce trends to keep an eye on this year.


Long, boring product descriptions have taken a backseat to much more visual experiences. These days, consumers prefer eye-catching visuals that give them a look into their products. Physical stores give you the liberty of viewing a product that interests you. The same can be said about online shopping as well. However, it does not end there. We’re not talking images and videos of your product. We mean high-quality visuals that are backed by artificial intelligence. This year we’re bound to start seeing more augmented reality experiences being baked into the shopping experience.  

Sounds cool, but how does it work? Let’s say you want to buy a lamp for your bedroom. You’ve decided on the one you like, but how do you know if it will look good in your bedroom? Integrating AR helps give your customer a sense of what the product will look like in a real-world environment. It allows consumers to zoom in, turn around, and view every part of a product that they are interested in. All in all augmented experiences and innovative visualizations are definitely on the list for 2019.


Yes, online shopping is starting to overtake physical stores, but it looks like the latter has resurrected from its grave. Amazon, the world’s largest and strongest eCommerce giant put up a very real, very physical, brick and mortar store at the big apple, New York. But why would a benchmark performer in the eCommerce industry put up a physical store? Kind of defeats the purpose, don’t you think? You would be wrong. Consumers flocked to this outlet, and Alibaba, Amazon’s competition from the east followed suit by setting up an Alibaba store as well. In fact, these stores are a sight to behold. They are architected the same way that it looks on the website or app. For example, the Amazon store has categorized the aisle according to various headings that you find on the website, like “trending now”, “most relevant”, etc.

Digital kiosks are newly trending as well. A digital kiosk works pretty much like digital signage, by offering product details and visualization. However, these kiosks are more than just a platform to advertise your product. Customers can view products that are not available on the store, click on the purchase code, and opt for home delivery of the same. Just like your online shopping experience, but in a physical store.


In 2019 machine learning will propel the shopping experience to a whole other level. Picture this. Online shoppers are given smart product bundle recommendations that fit their purchase behavior, while on the merchant’s side, machine learning delivers accurate forecasts of sales trends, by location, timeframes and down to individual product SKUs. Machine learning delivers a win-win solution for both merchants and shoppers. Machine Learning solutions such as Curve’s will also be of utmost importance as far as driving data insights are concerned.

Combining these trends can prove to be extremely beneficial for your e-Commerce business. The year has already started, so plan out your business strategies with these new trends.