Crealyitcs Insights

Break down silos in ecommerce to drive performance

Getting OmniChannel Right – Pairing Online and Offline Strategies to Maximize Sales


In business magazines and online publications, there has been a lot of doom and gloom regarding the retail industry in recent years. You hear stories of large retailers closing, malls emptying, and earnings slipping for some of the most well-known brands in the world. Despite the negative messaging, U.S. and worldwide trends are showing steady growth in retail markets following the recession:


Those big headlines might pull in visitors, but they fail to reflect the reality of the growing retail industry. Companies across the world are finding new, innovative ways to connect with their customers and provide a consistent experience wherever those interactions happen.

Omnichannel marketing plays a key role in the success of retail stores today. According to Google, 84% of smartphone shoppers use their phones to research products while in a physical store. Increasingly, customers expect a seamless experience between digital and in-store interactions.

What is OmniChannel?

So, what is omnichannel? The term itself has become a bit of a business buzzword, but the practice has real-world implications for any retailer. Omni comes from the word “Omnis,” which means “all” or “universal” in Latin.

Omnichannel refers to a company’s ability to provide a seamless experience no matter where they engage with customers — whether it is in person, through phone, or on their website. Omnichannel strategies are about true continuity of the customer experience, no matter where they interact with a company. In the early days of eCommerce, as larger retailers began to flesh out their online offerings, their online presence was often disjointed from their in-store offerings.

This disjointed feeling creates a disconnect between customers and brands. In the early days of eCommerce, this was expected by customers, they didn’t have the frame of reference to expect any different. But times have changed, and consumers are beginning to expect experiences that feel more centralized. Being able to track what a user does through online channels and apply those insights to interactions through other channels provides measurable benefits. It helps to facilitate engaged, loyal customers. The truth is that customers choose to interact with companies through multiple channels for a variety of reasons. For instance, the reasons why customers generally to shop in store as opposed to online can vary quite a bit:

why us consumers shop.jpg
Image Source: Business Insider

As the industry has matured, many companies have found ways to improve the customer experience across channels. Still, there is a lot to learn.

Understand the Customer’s Journey

In order to provide a seamless experience across multiple channels, it’s important that companies are able to understand the customer’s journey in full. Understanding the most prevalent paths taken by your own customers will allow you to focus your efforts on smoothing over issues that apply directly to them. Customers are increasingly using multiple devices during the transactional process.  A user may begin this process on their desktop, researching the product and company. Later, they may add a product to their cart while using their phone before finalizing their purchase several hours later on their tablet.

If that process wasn’t facilitated, the company may lose the sale. Imagine that the user found that once they logged into their account from their tablet, that the item was no longer in their shopping cart. You are now asking the customer to take an additional action — one that they have already taken — in order to complete their purchase. Those types of redundancies always result in lower conversion rates. This type of omnichannel consideration is becoming an expectation among average consumers.

Other examples of omnichannel strategies could include allowing a customer to return an item using their online purchase record as proof of purchase, or using an online coupon at a physical retail location. These are small examples of how a lack of omnichannel thinking could be aggravating to a customer and ultimately push them toward taking their business elsewhere. While these examples are ones that most companies often cover, it provides a clear understanding of what people mean when they use the term “omnichannel.”

In this article, we laid out a few best practices for setting up your omnichannel strategy.

Segment Audiences and Increase Personalization

We are at the beginning of the era of “big data.” Companies are collecting more information about customers than they ever have before. Despite this fact, many companies struggle to put the information that they collect to good use. There is an unending number of ways to personalize the customer’s experience using the data that you already collect.

A simple and effective place to start with omnichannel personalization is through email. Using the data at your fingertips to ensure that you are delivering laser-targeted email messages to customers is vital for improving engagement and open rates for your email list. Use purchase data to personalize the emails that you send to every prospect, regardless of where the final purchases are made.

Segmentation is a powerful tool, and learning more about your users can help you to provide a more consistent experience across all channels. Customers prefer marketing that is tailored to their interests and habits. Using that data to improve omnichannel experiences helps companies to provide a consistent, reliable experience to their customers.

Empower Sales Associates

Image Source: Dose Media

In physical retail locations, one of the most common omnichannel disconnects comes from sales associates’ not having the tools that they need to help customers in an omnichannel environment. Your sales team should be armed with tablets and mobile devices that allow them to access important product information, promotions, and customer information that will assist them in providing a better shopping experience. Even simply referencing an action that a customer on your website can impress and help to create a positive impression.

According to a recent study from PWC, 78% of customers want sales associates with a deep knowledge of the product. While companies with a large number of products will have a hard time training every employee on the intricacies of every product – empowering your team with information at their fingertips while engaging with customers certainly helps to bridge that gap.

Too many companies look at omnichannel success purely from a marketing perspective. We invite retailers to take a step back and see that true omnichannel success is about human interaction. A personalized email is great, but arming sales associates with your customer history provides a truly seamless experience.

Develop Omnichannel Content and Improve Accessibility

It’s no secret that customers love reading and using content throughout the customer journey. Why then, is all of the focus on providing content to customers online, with so little placed on providing that same content to in-store shoppers? Improving the accessibility of the content that you have already invested in is a great way to improve your omnichannel presence and find ways to give in-store customers access to content that helps with their buying decision.

Connect Customer Service Online and Offline

One of the most aggravating omnichannel mistakes for customers is a lack of connection between online and offline customer support options. All companies boast about their world-class customer support — well, true world-class customer support isn’t limited by where the interaction took place. Poor customer support experiences erode customer loyalty.

According to a recent study by Aberdeen Group, companies with the strongest omnichannel customer engagement strategies are able to retain 89% of their customers. Compare this to the 33% of customers retained by companies with weak omnichannel implementations and the benefit of uniting support channels becomes crystal-clear.

Your customer service and support teams are often the first point of contact that a customer has with your company. They are responsible for creating that first impression or improving the relationship. Make sure that you are arming customer support reps with customer data across multiple channels to provide as seamless of an experience as you can.

Measuring Success in an Omnichannel Environment

One major challenge at the heart of any omnichannel strategy is tracking attribution: how to accurately reward different channels along the multi-channel customer journey for their contribution to a sale. It’s an important problem to solve so you know which channels to invest more in, which to drop and which to rethink.

Bridging the gap between online and offline media channels is no small feat. All the current solutions have their drawbacks whether that be complexity or coverage. But, to get an accurate picture of your activity, you need to try to express your marketing success metrics in an omnichannel way – the sum of in-channel conversions and influenced conversions in other channels.

In this article, we give an in-depth picture of how to attempt more accurate omnichannel tracking with today’s solutions and give you a preview into new technologies that will improve our understanding of omnichannel attribution.

Channel Lines Will Continue to Blur


In the grand scheme of things, the focus on omnichannel strategies is still relatively young in the world of retail business. Growth in tech has lead to an increase in solutions to bridge these gaps, and already we see the channel lines beginning to blur. As time goes on, it will become even more difficult for customers to separate their experiences with companies on different channels. By adopting these strategies now, eCommerce companies put themselves at the forefront of a business revolution that is certain to grow.

Creating better omnichannel experiences is a process. It won’t happen overnight for any company. However, identifying gaps in the customer experience now can help to illuminate a clear path for any company that would like to improve the way they communicate with customers across channels.

Why Lifetime Value is the Most Important Metric in eCommerce

If you were one of the kids who sat in algebra class, half paying attention, wondering when you would ever use what you are learning – it’s time to dust off those algebra skills. In eCommerce, we spend a lot of time sifting through a long list of metrics. Conversion percentages, new customer rates, cost per order — it can all get a little overwhelming. But, what if I told you that there was one metric to rule them all? One singular metric that you could use to inform all future marketing and sales decisions and increase your bottom line?

Enter, customer lifetime value (CLV).

In eCommerce, CLV is the value that a customer will contribute to your company over their entire “lifetime” (usually 12-24 months). Essentially, it is the amount of money that they will spend on your products and services after the expenses of acquiring them as a customer. There are numerous types of CLV. The two most popular forms of CLV calculations are historic and predictive.

Historic CLV is a simple calculation. It is the sum of the gross profit from historic purchases made by a specific customer. This takes into account the expenses associated with the purchases that the person made.

Predictive CLV is generally a more worthwhile metric, albeit a bit more complicated to produce. Predictive CLV uses previous transactions, mixed with a variety of behavioral indicators that forecast a lifetime value for an individual customer. With each new purchase and new behavioral data, the Predictive CLV will change and become more accurate over time.

Why is Customer Life Value the Most Important eCommerce Metric?

Source: Kissmetrics

Customer Lifetime Value is an extremely important in eCommerce applications. In digital marketing, it gained prominence with the rise of software-as-a-service but quickly found its way into eCommerce as well. The value of the metric has made it a staple among modern eCommerce businesses.

CLV is the single most important metric for measuring gross profit and success over time. The most expensive endeavor for eCommerce businesses is generating new customers. Customer acquisition can be cost prohibitive, and returns are often difficult to forecast. CLV attempts to answer that question.

Knowing the CLV of a customer will help you to strike the ideal balance between customer retention and acquisition. Knowing at what point a customer becomes profitable, is an essential part of knowing how much budget you can allocate to a particular channel or market.

Additionally, CLV provides real insights into your customer retention strategy. A steadily climbing average CLV shows that your retention and upselling efforts are paying off and having a real effect on your customer’s chances of returning.

Calculating CLV

In order to make use of CLV in your eCommerce business, you first have to know how to calculate it. As we said earlier, there are multiple CLV versions that are commonly used. Let’s look at how both historic and predictive CLV, the two most common, are calculated:

Historic CLV

Historic CLV is a straightforward metric. You simply add all of the gross profit value up from all of their transactions. Here is the equation:

Historic CLV = (Transaction1+Transaction2+Transaction3…) X AverageGrossMargin

This is simple enough to be calculated in Excel as long as you have all of your transactional data on hand for a given customer. This should also take into account any expenses like service costs, returns, acquisition costs and other expenses to provide a clear picture of individual profit.

Of course, it can be complex to put together these expenses on an individual basis. Attributing certain costs to an individual customer is often problematic. When in doubt, use average to estimate until you can properly track expenses individually.

Predictive CLV

Predictive CLV tries to obtain an accurate CLV value for past and future purchases within your company. Here is the equation:

PredictiveCLV = ((AverageMonthlyTransactions x AverageOrderValue) AverageGrossMargin) AverageCustomerLifespanInMonths

This is a simple way to calculate predictive customer lifetime value. It provides a good picture of what the value of each individual customer is for your business. With that said — every industry is different and you may have to make specific changes to your CLV equation over time to have it accurately reflect the value of customers. There are more advanced versions of the Predictive CLV algorithm out there, and you should explore how well those options may fit your business model.


Return on Ad Spend (ROAS) is the most commonly used profitability metric in eCommerce. It measures how much money you get back for every dollar that you spend on advertising. While similar to standard ROI metrics, it provides specific measurements for each individual marketing channel.

You calculate ROAS using this formula:

ROAS = (Revenue – cost) / Cost

While both CLV and ROAS have their place, it is important that you not rely too heavily on ROAS  to gauge overall performance. ROAS-based models focus on whether your advertising is efficient but ignore if that’s the most effective way of growing your business. ROAS is all about winning that impression, click or customer engagement, but it doesn’t take into account the ultimate business measurements of profitability, margins, and new customer acquisition.

Customer Lifetime Value provides a bigger picture look at the value of each customer and sheds light on the real world effect process changes are having within your company. While both metrics attempt to account for the expenses and spending associated with every purchase, only CLV provides a clear long-term picture of expected profits from individual accounts.

Getting Everyone Onboard with CLV


You may find it difficult to get everyone on board with integrating CLV into your daily workflows for a few different reasons. Primarily, people like to stick to the status quo and are resistant to change when current systems are “working,” despite the benefits that CLV could bring to the table. A few strategies that you can use to bring the rest of your team on board include:

Find an Advocate

Chances are, you aren’t the only person that sees the value in optimizing for CLV. Ask around, and see if you can find another advocate for your changes. Try looking outside your own department as well. One of the benefits of optimizing for CLV is that, unlike ROAS, it can have implications in other departments like Customer Retention and Merchandising.

Present the Facts

If you can’t find someone that understands the value, you’ll have to put it on display. Try to schedule a small meeting with relevant stakeholders that can help you to implement CLV into your workflows, and present them the benefits of doing so. Try to include real-world examples of CLV being used by eCommerce businesses.

Offer a Trial

Your team will be unlikely to re-work all processes to include CLV without seeing it in action first. Try to identify a few small areas of your business where implementing CLV into the workflows would make a substantial difference, and ask for approval to use it within those contexts. PLAs provide a great place to test this kind of optimization. You can select a small group of products and see what optimizing for CLV does over time and compare it with a similar set of products that are optimized for ROAS.

Customer Satisfaction and CLV


One important thing to consider with CLV is the fact that customer satisfaction (CSAT) plays a huge role. The better your customer service is, the higher the lifetime value of each customer will be. Great customer service makes them more likely they are to buy from you in the future and stick around as a customer. With that said, poor customer service can also have a large negative impact on your CLV data as well.

Adopting CLV

Customer Lifetime Value provides important insight into your operations as a whole. The big question is how much you should spend on all your advertising channels in order to achieve your total long-term revenue goals. Any eCommerce business should implement and use it frequently to measure their marketing and sales efforts.

Although it is a relatively well-known concept at this point, older eCommerce companies may be reluctant to adopt it and instead opt for more traditional metrics. In these cases, it is important to lobby for its usage and show examples of how it could have helped your business. Our research shows that when advertisers focus on long-term revenue goals, they make about 5 percent more revenue in the first year than when they focus on short-term goals like ROAS.

CLV can help to shed light on the areas of your business that must improve to increase your bottom line. Knowing customer lifetime value and profitability at the product level allows for improved paid media placement, intelligence in product pricing, and better inventory optimization.

The New Price Elasticity Model Everyone Should Be Using

The traditional understanding of Price Elasticity focuses on the influence of product price on sales of a particular product. But price also strongly impacts Google Shopping performance – which is used by most online retailers to acquire new customers and maximize Customer Lifetime Value through repeat purchases. Because of this connection, price decision makers and marketing campaign managers need to start looking at an extended model of Price Elasticity that also accounts for the impact of price changes on advertising cost and performance.

“Pricing is the most effective profit lever.”

This statement from Robert J. Dolan made in 1996, holds true now more than ever. Price’s impact on business is much bigger than just on sales volumes and margins. Prices have become a fundamental part of online advertising, not just on Google, but also on other PLA based ad networks.

In terms of Product Advertising success, price plays a huge role in two places:

  1. Frontend: Prices (and price changes) have become a major visual element in online ads.
  2. Backend: deep within the auction algorithms, prices and their competitiveness are important criteria for Google and other PLA based networks to select which products to show – and how often.

Let’s take a look at each of these in depth to see how exactly price changes affect Product Advertising success.

Visualizing prices in ads is just the tip of the iceberg

The rise of feed-based advertising has made it easier for customers to compare prices than ever before. Google constantly experiments with how to visualize prices, price slashes, and promotions:

Example: Price slashes, price drops, special offers. Image courtesy of Merkle.

These experiments show just how important price has become as a visual element to Google and those who shop there.

Algorithms decide which products to show based on price

It should come as no surprise then that Google takes price into account when deciding which products to showcase in the paid search results (Google Shopping) and in what order. Crealytics has conducted research on the role of price in Google Shopping, and the results show that competitively priced products perform significantly better in terms of traffic acquisition than those that are more expensive:

This information leaves retailers with two important levers to operate when trying to increase sales through Product Advertising: Product Price and Product Bid (MAX CPC). In order to drive more sales, a retailer can either increase advertising budgets, decrease product prices, or a combination of the two.

The example below shows two scenarios that explain when pulling each of these levers independently.

While increasing advertising spend can significantly increase the number of impressions and sales, it pales in comparison to the performance uplift we get from lowering the price. Ideally, both levers would be used in combination.

Should next generation pricing decisions consider sacrificing product margin in return for more and cheaper advertising clicks and subsequent conversions?

In order to make sense of both effects, we propose an extension to the current understanding of Price Elasticity of Demand.

Elasticity of Demand

Traditionally, Price Elasticity of Demand researches how the sales of a product are affected when raising or lowering its price. Elastic basically means ‘responsive’:

Lower / higher price refer to market average price. More sales / fewer sales refer to sales make with market average prices.

But, the traditional model of price elasticity does not measure the impact of a price change on advertising performance for online retailers, e.g. the advertising costs incurred to acquire a new customer and to sell products.

Elasticity of Product Ad performance

When managing Google Shopping campaigns, we observed the following phenomenon:

We, therefore, propose to extend the model to include the secondary effects of advertising. It is similar in that it helps to explain the impact of price change on advertising performance.

Benefits of the new Price Elasticity model

Online advertising is a decisive instrument for new customer acquisition and for customer lifetime value optimization through repeated purchases. As Google Shopping and other PLA based ad networks use product prices as an algorithmic signal, prices do have a strong influence on product ad performance in terms of total reach, cost and conversion. Alas, the traditional Price Elasticity model is blind to this kind of impact.

We believe that better price making decisions can be made by breaking down data silos to understand and include the impact of price changes on advertising performance. Armed with that knowledge, companies can stop focusing on departmental efficiency metrics and start to optimize for enterprise level profitability.

The Future of Retail – How Technology Will Change the Way We Shop

Throughout history changes in technology have changed the way consumers interact with and buy products. New advancements bring easier access to products and easier advertising from brands. Early on, advancements that were not specific to the retail sector perhaps had the largest effect on the industry.

There have been many innovations throughout the years that we overlook or take for granted. The first mall opened in Lake Forest, Illinois in 1918. In 1952, barcodes were invented, allowing for better organization and faster checkout. 1978 marked the debut of the first point-of-sale system. These are excellent examples of game-changing technology that changed the face of retail forever. In the last three decades, that slow crawl of advancement has become a dead sprint that is still picking up speed.

Whether consumers realize it or not, we are seeing an extremely fast evolution in the market even today. Starting with the rise of the internet, the entire landscape of retail markets looks completely different to how it did just a few years previous.

Let’s take a look at the principles and trends that will shape the future of technology and the retail industry as a whole.

Customers are More Informed than Ever

Without a doubt, customers have access to more information than ever before. While some might see this as a boon to competition, companies that create great products can only benefit from this fact. In seconds customers can check the price of the item in stores around the world, read reviews from other customers that have purchased the item, and learn about the company that they are purchasing from.

Ad platforms like Google Shopping, even do the majority of work for the consumer by aggregating similar products from multiple retailers and surfacing them in a simple interface for consumers to choose from.

81% of shoppers research online before making a purchase. Those customers are becoming increasingly wary of the marketing that they interact with. According to Nielsen, confidence is declining rapidly in television ads (down 24%), magazines (down 20%), and newspapers (down 25%). Increasingly, consumers are relying on a variety of sources and their own research and intuition to decide what to buy.


On the whole, this leads to better, more effective research and higher expectations among your average consumer. To meet these increased consumer demands, retailers have been forced to adopt new technologies to fill in the gaps. In addition, retailers need to be increasingly aware of what their competition is doing so as not to be caught off guard by promotions or discounts that may affect sales.

Consumer Expectations and Instant Retail Gratification

Consumer expectations in retail are changing rapidly. The Internet has given rise to a culture of instant gratification. Information and entertainment are available to anyone within seconds. In the U.S., 21% of consumers are interacting with the internet “almost constantly.” According to ChartBeat, 55% of page views last 15-seconds or less.

Source: ChartBeat

As eCommerce deliveries become faster, using programs like Amazon’s free same-day delivery program, consumer expectations shift. With the FAA slowly crawling toward regulations to allow drone deliveries, delivery times could shrink to a few short hours in the coming decade. Companies will be forced to open more distribution centers and infrastructure to meet these demands. As such, being able to accurately manage inventory turnover rates becomes even more important.

It’s important that eCommerce companies are able to recognize these trends and shape their services around them. Customers have come to expect a faster, more responsive service from companies. These expectations don’t change online either, where retailers are located around the world.

Automated Purchasing

Another huge shift in retail and eCommerce has come from automated purchases. In the future, consumers will likely have certain items automatically shipped to their house on a monthly or weekly basis. This removes the need to go to the local grocery store (or order online) to secure their essentials. Anything that is an essential home product has the potential for automated replenishment.


The Amazon Dash button is one recent example of automated purchasing. Solutions like this may well be the future of eCommerce and online shopping. Every button is assigned to a specific product. When the customer is running low, a simple press of the button automatically orders the product for delivery. The customer doesn’t even have to give the purchase a second thought.

Moving forward, the smart bet is on automated purchasing becoming a much larger part of retail shopping. This is particularly true for items that need to be regularly replenished within the home. Soon we may see smart appliances that detect shortages. Imagine a refrigerator that detects when you are low on milk, and automatically adds it to your next delivery.

Another form of automated purchasing of essentials that we have seen recently comes in the form of subscription services, which have become increasingly popular over the last five years.

Subscription Shopping


In many categories, monthly subscriptions are disrupting industries. In some cases, subscription services have the potential for completely supplanting traditional retail. The subscription model is ideal for retailers because it locks customers into purchasing a particular product from them. The model gained popularity online, with companies like Dollar Shave Club offering an essential product for a low monthly price. Gillette quickly followed suit with their own similar service, giving credence to a change in industry norms.

Following these examples, we’ve seen subscription services rise in popularity in other categories. Categories like makeup and beauty (BirchBox), food (Blue Apron), and clothes (Trunk Club) have all seen subscription products pop up.

Retailers and eCommerce companies should prepare for a future where monthly subscriptions for essential items become the norm. We could soon see many other categories disrupted by subscription services. Consumers favor options that take the work out of shopping for items that they will need to purchase.

A New Retail Frontier

Retail companies have always had to adapt to changing technologies to stay with the times. However, we have never seen the rapid innovations that we have in the last three decades. The speed of these changes will accelerate, leaving inflexible companies scrambling to adapt. Customers have more access to information than ever before. They are increasingly looking for ways to automate their shopping. With shoppers favoring instant gratification, it is important for eCommerce companies to adapt to stand out from their competition.

Understanding Price Elasticity in eCommerce

Choosing the right price for each product can be a difficult task. Following our last post on dynamic pricing, it seems important to cover price elasticity, which plays a huge role in price optimization in e-Commerce. If you’ve ever taken an Econ 101 course in college, you have probably calculated price elasticity. Determining the price elasticity for your products allows you to run better tests and make informed pricing optimization decisions.

What is Price Elasticity?

It’s assumed that more customers will buy a product when it’s cheaper, and less will buy it when it is expensive. This follows the basic principles of supply and demand and nearly always holds true. But how many more people will buy when you lower the price? How many fewer people would buy that same product if you raised the price? The price elasticity of demand is a concept that answers this question.

Price elasticity attempts to show exactly how responsive demand is for a product, based on how it is priced. When contemplating a pricing change, understanding how elastic or inelastic your products are is critical. Elastic products are sensitive to changes in price. Inelastic products are not sensitive to changes in price and demand. Knowing the elasticity of products can help you to improve pricing tests and find your optimized price quickly.

Some products are clearly elastic, and show immediate and sometimes dramatic responses to changes in price. There are many reasons why a product may sell well at one price, but not so well at even a slightly higher price. Some of the common reasons why a product may be price elastic include:

  • The pricing change has placed the product above average market value. If you increase the price of an item above that of your competition, sales may decline. With some very elastic products, that decline may be substantial for even a modest price increase.
  • The item is non-essential. Non-essential items are typically elastic and sensitive to changes in price. With non-essential products, there may be a price point where consumers refuse to buy.
  • There are other substitutes readily available. If the price of the PlayStation 4 were to rise by $250, more consumers would opt to purchase the XBox One. When substitutes are available at lower prices, elastic products will see huge fluctuations in sales figures.

Now, all products are elastic to some extent. You’d be hard-pressed to find a product that doesn’t see its sales figures shift when prices rise or fall dramatically, but certain products are necessary to consumers regardless of price. Gasoline, for instance, is a popular example of a product with inelastic demand. When gasoline prices rise, the demand for the product may decrease slightly, but not by much.

How is Price Elasticity Calculated?

Here is the most common formula for calculating price elasticity of demand:

Price elasticity of demand = Percentage change in quantity demanded / percentage change in price.

Let’s use this formula in an example. Let’s say that a furniture company increased the price of a table from $300 to $360. This is a price increase of 20%. You would expect this substantial hike to result in fewer sales.

Now let’s pretend that this price change resulted in a change in quantity sold from 100 units to 70 units. The percentage of demand decrease is -30%. Now, using the formula let’s solve for the price elasticity of demand:

-.30 / .20 = -1.5.

In this example, the price elasticity of the table is 1.5. The negative is ignored and the absolute value is used to represent price elasticity. It is the distance from zero that we are interested in measuring. When a product has a higher price elasticity value, customers are more sensitive to changes in price for that product.

Testing Price Elasticity with Product Advertising

Product advertising is an excellent way to run price elasticity tests. Experienced eCommerce companies likely have a good idea which of their products are elastic and which are inelastic, but running tests can return some surprising results.

In fact, search engine product advertisements may be the best way to test elasticity. With an understanding of price elasticity, you can use that data to inform more tests to determine optimal pricing for your products. There are a few reasons why product advertising makes an excellent testing ground:

  • Fast results. Product advertising generates results much more quickly than waiting for customers to organically find your products and purchase them. You can quickly generate elasticity data by increasing your advertising spend on specific items.
  • Easily controlled variables. You can set specific ads to run at certain times during the day, week, or month. You can ensure that outside influences play as little role in the sales process as possible.
  • Automation. With tools, you can automate the testing of price elasticity and even price optimization among hundreds or thousands of products at a time. This data can provide huge returns and with automation, cost very little.

Discounting a product helps you to acquire more customers, but the question is where the optimal return lies. Let’s take a look at an example. Let’s assume that the product in this example has a per-unit cost of $50.

After testing a product’s pricing, you generated the sales figures outlined in the graph. At your highest price of $120, you generated 10 sales. At your lowest price of $80, you generated 60 sales. This is a 600% increase in sales. This example shows us that this product is price elastic, in that its sales are sensitive to changes in pricing. But which price point generated the most profits?

While discounts will certainly help you to acquire more customers or get rid of excess inventory, it also greatly decreases your margins, affecting your profits. So, based on the tests run in this example, which pricing level would be optimal? To figure this out, we have to look at the profit generated at each price point.


The test showed that the product generated the most profit at a $90 pricing. Of course, there are many variables that have to be considered before you can accept this as the true optimized price for the item, but it does provide you with an excellent starting point for further testing.

Factors such as the time of year, time of day, and traffic source all play a critical role in how products sell. eCommerce companies should do their best to control these variables. Product advertising allows you to control these variables and limit outside influences. Ideally, you should test items at different prices until you reach statistical significance to determine optimal pricing.

You can also factor in your Advertising Cost when you calculate Price Elasticity. Our tests have shown that as you raise your prices, you will need to spend more advertising budget to achieve the same impression volume. This additional budget should be another factor in your profit analysis.

Using Price Elasticity to Inform Optimization Testing

The real value in understanding the price elasticity of products in eCommerce is the data that it provides. Understanding how elastic your products are allows you to make better testing decisions for each product. Items with a higher elasticity will have to undergo a wider range of tests to determine optimized price, while inelastic (or less elastic) products have a much smaller potential pricing window.

What is Dynamic Pricing and Why is it Important?

Dynamic pricing is an e-commerce and retail strategy that applies variable pricing instead of the more typical fixed pricing. As more data is analyzed, optimal prices for items are calculated. The time between price changes depends upon the business and item, but can be as often as every day, or even every hour.

Dynamic pricing strategy isn’t a new thing. In the past, pricing was influenced solely by demand and supply in a locality. How many people want to buy the product? How much inventory of the product is currently available? Is the item perishable? Will the item be replaced by a newer version at any point in the near future? These are all the types of questions that play a big role in traditional pricing.

Dynamic pricing uses advanced data, including data from some of the previously posed questions. Dynamic pricing is often an automated process that looks at more than just the traditional factors.

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LA, here we come!

Our team couldn’t be more excited to speak and exhibit at’s 2017 Digital Retail Conference, which will be held September 25-27 at the Los Angeles Convention Center. is the annual eCommerce conference for digital retail thinkers and doers! They’ve created a new immersive experience that blends insightful and actionable educational content, an easily navigable EXPO floor full of futuristic tech solutions and engaging new ways to expand your professional network.

It’ll be a busy conference, but make sure you set aside 20 minutes to see our founder Andreas Reiffen give a tech talk on Breaking Down Silos in Marketing, Pricing, and Inventory at 9am on Wednesday 27th on Tech Talk Stage 4.

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3 Reports to Optimize Your Procurement Strategy

Are you buying too much stock, stuck with deadstock, purchasing the wrong products, or pricing products ineffectively? In order to refine your procurement strategy, you should be tracking all of these aspects.

TradeGecko recommends these three reports (Yield Management, Inventory Turnover, and Merchandising Strategies) to help you increase efficiency and profitability, whilst allowing you to optimize your procurement strategy:

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How competitive intelligence can maximize your ROAS

Digital advertising spend in retail eclipses all other industries, but at such a substantial cost, everyone selling online wants to know how they can boost their return on ad spend (RoAS). eMarketer reported in 2016 that retailers spent $16 billion on paid digital advertising and forecasted that figure would jump to $23 billion by 2020.

Marketers in retail have a wide range of responsibilities to get customers in the physical or virtual door, such as driving brand awareness, customer loyalty, and retention. The role also covers increasing website and in-store traffic and multi-channel growth. Not to mention, development and management of best-in-class eCommerce and integrated marketing strategies that increase the retailer’s digital footprint.

All of these central tasks that make up a marketer’s role in retail all boil down to traffic and conversions. The questions that keep retail marketers up at night include: are we getting enough traffic to hit our sales and revenue projections? If not, how do we drive more people to our stores and website to buy? Digital advertising helps with this, but with the massive amount retailers are pouring into ads, maximizing the return on that ad spend is only half of the challenge. The other side is from a competitive intelligence standpoint. All retail marketers should ask themselves often: do we have a good idea of what our true tier one competitors are doing from a marketing perspective?

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3 Best Practices for Dynamic Remarketing Ads

With Audience Targeting dominating the foreseeable future of Search Engine Ads, familiarizing yourself with Retargeting Options may be useful. Dynamic Remarketing Ads can massively improve your performance by allowing you to help build leads and sales by bringing previous visitors back, who may have left at different stages of the transaction. Before we get to some of the best practices for utilizing Dynamic Remarketing Ads, let’s take a step back, and recap what they are.

What are Dynamic Remarketing Ads?

Since the release of Dynamic Remarketing Ads back in 2013, marketers are able to re-engage with former site visitors with highly customized ads displaying the same and/or similar products they previously looked at. The aim, of course, is to convert them into customers.

So, while prospects are still in the early stages of their purchase, you get to continue engaging with them with tailored messages.

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