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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 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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Image testing in Google Shopping: the next frontier

Any digital marketer worth their salt knows that testing, measuring and iterating are the three pillars of a successful strategy.

Google Shopping, however, has proved somewhat resistant to this strategy. Unlike other methods of PPC, it’s technically not possible to properly split test alternative titles by showing two different versions of the same ad simultaneously to different people.

The obvious workaround is to compare two different time periods, and while that does come with some challenges, it’s still possible to draw significant conclusions. To help ensure the different time periods aren’t the reason for any uplift/downswing, we also analyze the total performance of all the products over the whole time period.

In their simplest form, Shopping ads are made up of a Product title, description, category, and image. We’ve had significant success in testing the first three over the years – you can read about those findings here – but image true testing has remained somewhat elusive.

In this post, we’ll discuss the current challenges associated with image testing, what testing we’ve done thus far and the insights we’ve derived.

Image testing challenges

An image can tell you far more about a product than a title or a description and a good one is key to catching the attention of would-be customers. Images are widely believed to be the most important factor in shoppers choosing to click on an ad.

Image testing looks to be the next game-changer for click-through and conversion rates, but it’s still a bit of a black box. This is largely due to three factors that make images difficult to test: categorization, image displays, and time lag.

Image categorization

The first issue comes down to how you categorize your images, to begin with. In fashion, for example, a basic image test would be to see whether images with a model perform better than images with just the product in them. However, if you haven’t already categorized your images in this way already, it will be difficult to know which images to change.

Ideally, you’d change all the images in an entire category. But this also means you need to have an image of both types for every product in that category. Which you may not have, especially if you sell products from other brands.

Image categorization is time-consuming and largely manual. However, without accurate categorization, you won’t be able to run a conclusive test.

Conclusion: Spend time categorizing your images along all the lines you think you’d want to test them

Image display

While image categorization is something completely within your control, whether or not your image is even shown by Google is not.

On the main SERP (Search Engine Results Page) each of the (up to 8) products shown has an image. However, in the Shopping tab products get clustered into just one offer list. This usually happens when multiple retailers sell the same product.

Effectively, what this means is that you cannot be sure your image is being shown – making accurate testing very difficult.

Conclusion: Unfortunately there’s no real workaround for this as you don’t have any control over which image is shown and where. For more general tests you could test only exclusive products not sold by anyone else, in which case you can be sure that your image is displayed

Time lag

Another factor out of your control which makes image testing difficult is the time lag. In this instance, time lag refers to the amount of time after you change the image on your website for Google to change the image on your Shopping ad.

It can take up to 72 hours for Google to index a new image when the accompanying URL is changed. If you don’t change the URL and instead do a server-side image swap, re-indexing the image can take up to 6 weeks!

This time lag makes image testing take a while because, in order to accurately measure the effect, you need to wait for all the images to be indexed and then run your test, change them, wait for the re-indexing and run the test again. The whole process could potentially take months.

Conclusion: Make sure your images have changed before you start collecting data for your test – wait at least 72 hours.

Image testing and insights

Despite the challenges accurate image testing presented, we were able to run a test that gave us an interesting insight into an image’s potential to boost a campaign.

The data we used came from two retailers in the fashion industry. For this first iteration, we looked at the effects of using images that featured a modeled product and a product in isolation.

In total, we changed around 1800 images. Up to 40 million impressions were taken into account, and we overlooked any products that were not consistently available. To help measure the true impact of the new image, we also ran a control stream as a baseline.

Interestingly, we found that while in some cases changing the image had a significant impact on the CTR, in other cases it had very little effect.

When we dug a little deeper we found that whether or not an image change had a significant effect depended on the other images it was displayed beside in Shopping. If the image types in Google Shopping varied regularly (ie there was a roughly equal amount of images with and without a model), there was no significant benefit in having the image feature a model.

On the other hand, if most of the other Shopping images featured products on their own, it was beneficial to have an image that stood out (ie one with a model). We observed a 27% increase in CTR when our image stood out.

This presents another major issue with image optimization: knowing what sort of image will stand out. Figuring out what the most commonly displayed images look like for the top 1,000 products you sell presents plenty of its own challenges.

So close, and yet, so far

As Google gets better and better at figuring out synonyms and directing traffic to the right products, optimizing your product titles will get more and more difficult. Images have the potential to fill that gap.

The potential for image testing goes far beyond whether or not the image contains a model. Perhaps certain product colors stand out more than others. Or image background (white, color, scene) could be important.

For now, it appears that simply having an image that stands out from the competition in some way has the greatest effect. But as we pointed out before, even that isn’t an easy thing to figure out and optimize for.

There’s a long way to go before we get the full picture of what an image does to your campaign. And, honestly, it seems like we may need a few changes from Google before true testing and optimization are possible.

Nevertheless, we’ll keep plugging away at it to see what we can find out. We’ll keep you posted!

What do you think of image testing?

What Google’s Q1 2017 Earnings Report means for the retail sector

Yesterday, Google’s parent company Alphabet released their earnings report for the close of Q1 2017.

As we predicted, Alphabet’s revenues rose 17% between 1Q16 and 1Q17.  Much of that revenue boost is likely due to the 53% rise in clicks on paid advertising – no surprises there. What’s odd is that while both revenue and clicks went up, cost per clicks went down by 19%.

For those of you who paid attention in Econ101, you’re probably wondering how that’s possible. How can Google receive less revenue, but still make more profit?

Google claims that they have “refined their methodology for paid clicks and cost per click to include additional categories of TrueView engagement ads and exclude non-engagement based trial ad formats.”

But we think the answer is slightly more nuanced than that.

More ad inventory

First off, the sheer number of ads Google shows on a search results page has increased. Ads, most notably of the Shopping variety, have popped up in image searches, YouTube and even Gmail.

This “ad creep” has pushed organic results further and further down the page. In these two screenshots, for example, organic results didn’t even make it above the fold at all. Considering that Google is now reporting that 51% of all clicks are coming from Mobile devices, the lack of organic results means that advertising is particularly taking over the majority of the mobile SERP.

A large part of this creep is due to the growth of visually-oriented Shopping ads, where the image of the product is presented instead of the traditional three lines of text.  Sometimes known as PLAs, not only did this ad format increase the raw number of ads a searcher was presented with, it also increased the amount of space ads took up on the page – by a lot.

See, the reason that Shopping ads are so powerful is that they include an image of the product. And images take up a lot more vertical space than text.  

So if desktop SERPs contain 5 – 9 Shopping ads and 2 – 4 Text ads, your average human now has to scroll quite far down the page in order to click something that isn’t an ad. A task which becomes even more difficult when using a small phone screen – an important factor when you consider Mobile now accounts for the majority of online ad clicks.

More ads that take up more space means two things:

  1. Searchers are more likely to click on ads (equals more revenue for Google)
  2. There are more ads for companies to buy (increased supply initially leads to lower prices while demand catches up)

Visually oriented product ads

Secondly, the move towards Google Shopping Ads has traditionally lead to an increase in clicks in total. In their report Alphabet doesn’t differentiate the number of clicks generated by Shopping vs Search ads, but overall clicks on Google’s web properties (search, Gmail, and YouTube, etc) grew 53% from 2016 to 2017.

That means that Google is getting higher click through rates on existing space, because it can place three product ads in the same space as a single text ad, and consumers are more likely to click on image-based ads than text-based ones. According to our own research Shopping ads now represent around 74% of all ads clicked on Google.


This growth is also likely due to Google serving more product ads and expanding their availability to more general search terms — for example, showing Shopping ads on a search for “running shoes,” not just “Nike Air Max.”

In addition, Shopping ads have proved highly effective. Jessica Levens, director of e-commerce at Reef (a beachwear brand), recently said in the NY Times that “product campaigns helped triple sales that started from online queries, including instances where customers searched without including the Reef brand name.”

Our research also shows that Shopping ads are more likely to lead to a sale, making them a more profitable advertising medium. This is particularly impressive considering that in a side-by-side comparison, Shopping ads are actually more expensive than Text ads.

It’s no surprise then that retailers are snapping up them up. Shopping ads accounted for 52% of all Google search ad spending by retailers in the first quarter of 2017.

The important takeaways from this quarter’s Earnings Report are that

  1. Google has prioritized use of an ad medium (Shopping) that people click on a lot (More click revenue for Google)
  2. Google has used Shopping as a way to expand the number of available ads for retailers to buy (more ad selling opportunities for Google and lower prices while demand catches up to supply)
  3. Shopping has become an advertising medium that retailers can’t live without (always good for Google)

Everyone’s a winner (for now)

It seems all that traffic pushing and ad reshuffling is really working in Google’s favor.

In Google Shopping, Alphabet has created an advertising medium that works on multiple levels.  It’s good for consumers because they can easily find the product they are looking for, and it’s good for retailers who are getting a better CR and ROI than they were with Text ads.

What’s more, this ad medium is working on Mobile, which is a big deal considering it now equates to more than half of online traffic.

The real winners, as always, are Google. They’ve created a system where even though the cost of their product has more than halved in a year, they are selling enough of it to still make money.

What does this mean for advertisers?

Right now, Google Shopping is the deal of the century. Due to the ongoing availability of ad inventory supply, its costs are at an all-time low while the CR remains high.

This will not last forever! As more retailers recognize Google Shopping as a way of converting mobile traffic and improving the digital marketing ROI, they will invest more advertising money and CPCs will rise.

That means this is the best time to start investing in Google Shopping. Costs are relatively low, returns are high and competition is minimal. As a retailer if you can work out your Shopping strategy now, you’ll be in excellent shape when the rest of them catch on.

Department stores: a practical paid search guide to launching new markets

Last month, we explored the importance of launching paid search campaigns in different languages. In short: if people who don’t speak your native language buy from your store, your ability to target them with ads in their own language gives you a significant competitive advantage. But how do you actually launch new markets? For department stores who stock a range of products from different designers it can seem like a gargantuan task.

To launch paid search activity in a new market (Text Ads, Google Shopping or both), you need to be well prepared.  If you want to avoid AdWords creeping into your dreams whilst your launch date keeps getting postponed, here’s our step-by-step guide to help you get it right.

To keep things practical, we’ve based this guide on a real-life launch from one of our British clients who launched a new French account for their well-known department store.

By following the steps below, you’ll be well-equipped to take advantage of new, promising markets through your Text Ads and Google Shopping activity in no time.

Before you launch

Hold up! Before you dive in, there’s a whole lot of stuff that needs to be done. Launching successfully in a new market is all about preparation, so here’s how to get ready and set up like a pro.

1. Start early

Plan ideally two months in advance of the official launch date.  Make sure you have qualified resources in place, like a native speaker who can help with accurate translation and a multilingual website to receive traffic from the paid search activity.

2. Analyze

Be sure to analyze potential markets before making a decision. Ask yourself if it will be beneficial to tackle a brand-new territory, or go local in one of your most important regions. Look at performance metrics, such as clicks, impressions, CTR, cost and revenue, to help you make the best choice.

It’s crucial that you understand your company’s existing markets, as well as the new market you are attempting to enter. This involves evaluating any potential financial and economic implications of your expansion.

3. Keyword research

Start first with your brand campaigns, as these generally catch the most traffic and don’t need as much optimization as the others.

To build designer campaigns, you need to recognize all designers featured on your online store as keywords.

Finally, assemble your generic campaigns with the products you are selling online. This helps ensure that a significant number of search terms can convert.

You could also create long-tail keywords for your best-performing designers. For this task, you can take examples from pre-existing designer campaigns. Don’t produce long-tail keywords for every designer though, because they are more specific and tend to receive less search traffic. You can also use localized SQs (Search Queries) which are already performing well for existing campaigns in your native language.

Negative keywords are also important if you don’t want to spend money on undesirable search terms.

You might also want to translate ads from your existing account. Just remember to check if the name of your brand or designers have different meanings in the new language.

4.  Consider different designers

Align with every designer listed on your site regarding ad copy guidelines, so that any vocabulary that is specific to them can be defined. In the case of our client, we had to use the word “order” instead of “buy”, and “polyvalent” rather than “easy to wear”. The capitalization of letters might also be different in other languages, as well as the format of delivery costs.

Be careful with trademark issues too. Some designers may not whitelist you, thus prohibiting you from using their name in your ad copy. They might also request that you state clearly in the ads that yours is not the official website for their products.

Checking requirements like these goes beyond ad copy, including changes to elements such as ad extension or link structure. For instance, the word “shoes’’ used in a Final URL for our client had to be changed to the French ‘’chaussures’’. Cover all your bases.

Setting up the campaign

So, you’ve checked and double checked the preparations, and you’re ready to take this launch to the next level. Setup is one of those things that takes patience and a good eye for detail. Go steady and make sure you have the following covered…

1. Language

Don’t forget to change the language settings in the original account. You should exclude the new target language (in our account, the French one), from the original account settings. Failing to do this may result in your new Text or Google Shopping ads not displaying.

2. Bidding

Bid modifiers are an essential part of deciding where, when and how you want your ads to appear. Ads perform differently in each country, which means it’s necessary to alter their setup accordingly. There are different bid modifiers to look at when you make these changes: device, location, ad scheduling and RLSA (Remarketing List for Search Ads) – the impact of each should be analyzed to ensure the best performance in your new market.

To create the location bid modifiers in our own example, we made a geo analysis and added a positive bid adjustment for French cities generating high revenue and bearing a low COS. We added a negative percentage for cities performing badly. Paris, as the fashion capital, bears most of the traffic, and its bid was adjusted accordingly as you can see in the table below.

During launch

The show isn’t over once you hit launch; this is an ongoing process that needs care and attention to get it safely off the ground. Here are some tips to ensure your campaign stays on track once it’s live.

1. Tracking

Ensure new campaigns are tracked in your reports. It sounds obvious, but if they’re not included and set up correctly from the start, everything will be skewed. Check your existing report interface and template to make sure you’re correctly tracking activity.

2. Run SQRs

You should regularly run SQRs (Search Query Reports), using the results to help constantly build new keywords, adgroups and campaigns, and add negatives. The frequency of these queries will depend on the traffic your campaigns are capturing as well any additions to your website’s product offering.

3. Bid up aggressively

Push your bids – especially for mid and long-tail keywords – to drive as much traffic as possible through your campaigns at an early stage. This will make it easier for you to make relevant bidding decisions in the upcoming weeks.

Tip: Push designers or products which are important for your brand and revenue.

Also, be aware that new markets need more budget to gain traction, so prepare to funnel more spend towards these accounts to achieve best performance.

4. Analyze your bid modifiers’ performance

Regularly analyze your mobile bids, because it’s likely that their behavior in another language/region is different. To make changes on a bid level, don’t hesitate to optimize ad scheduling, which helps you manage the amount being spent according to performance and demand.

When helping our client expand into France, we decided after one month to increase the mobile bid modifiers for the designers that generated significant revenue. We also added ad scheduling with a higher percentage on Sundays – the day with the highest revenue.

5. A/B test new ad copy

To find the catchiest ad copy for your new market audience, make sure to test different USPs (Unique Selling Propositions). You can use the Lab Tab in Google AdWords to run different experiences and implement them if they show positive potential. The moral of the story: always experiment!

Little changes which might not seem relevant could make a huge difference, so play with  different Paths until you get the perfect mix.

6. Compare the performance of top areas

Here we can show from our own example how to compare performance of the top areas.

Clicks per category



One month after  launch, we observed that the clicks in the new French account (FR/FR) increased by 2429% compared to the  original English one (FR/EN), which considerably decreased. We predicted this outcome, because the likelihood of people in France searching with French – rather than English – terms is higher. The English ads are still delivering a minimal amount of traffic for the small number of non-French searches still taking place.

Clicks per device


We noticed a similar effect on different device levels, with mobile capturing the biggest cut of the traffic. From this insight, we could deduce that in France, French-speaking consumers tend to search using mobile, whilst non-French-speaking consumers search more actively on desktop/laptop.

Top Designers


The new French account also yielded more traffic thanks to the higher budget. We also observed the recurrence of one particular designer in both accounts, who appeared to be of French origin.


Looking at the results from our example with the UK department store, the launch of the client’s localized account was a success, triggering more traffic than the English one. We had to be patient when waiting to see any clear results, because when launching a new market, it can take weeks before the campaigns generate revenue.

Through our example, we also came to recognize that the top designers in one market may well perform differently in another new market. With this in mind, it’s important to stay on top of any bid optimizations that need to take place because of this divergence.

Keys to success

For search marketers attempting to expand into new markets, there are many steps to take, especially in the early setup stages of the account. The most important things to remember are:

  • You can’t be frugal – launching new markets requires extra budget to get them off the ground.
  • Experiment! – you have a lot to learn about your new market, and the best way to go about it is to test and experiment until you find out what works best.
  • Always employ negative keywords – you don’t want to waste money.
  • Focus on audiences and locations that yield the best performance – using bid modifiers to squeeze the most out of your top performers is a solid strategy.

If you’re thinking about launching Google Shopping activity in new markets, we’ve developed Camato to remove as many layers of manual work as possible. By automating campaign structuring and bid management, you’re left with more time to get to know your new customers.

Thinking of expanding into a new market? We can help.

Advanced Google Shopping: data insights from behind the scenes

At Crealytics, we love experimenting with Google Shopping to see what works and what doesn’t. There are all kinds of campaign optimization tricks to be discovered when you spend time testing. What’s more, as the hunger grows for more in-depth Google Shopping best practices, it’s crucial to stay on top of changes and developments in the Google’s algorithm and the sector itself. Luckily, we’re pretty nerdy when it comes to this kind of thing!

Last month at SMX West, I treated an audience to a presentation on Advanced Google Shopping, in the hope of addressing some of the biggest questions on the lips of PPC marketers today:

  • How should current changes in the Google Shopping economy affect my approach?
  • What impact does price have on performance and ranking?
  • How should I test my Google Shopping product images?
  • How can I ensure my product titles are performing?

I’ve compiled some of the most useful bits so that you can apply them to your Google Shopping strategies.

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