Category: Pricing Strategies

15 Jan 2019
Price Image

Using Price Image to Formulate Pricing Strategy

Price Image is how shoppers perceive a store’s pricing relative to its competitors. It is not the same as Price Index. Many more things go into establishing price image, including promotion programs, elasticities, seasonality, price ending numbers, and the overall design of a retailer store.

Price Index vs. Price Image

Price optimization solutions that are available today are based on rules and price indices that exclude your desired price image. What is needed are psychological models that measure your consumers’ perception of your pricing AND predict the impact of price changes on that image.

At its core, Price Image takes customer excitement into account. Whereas Price Index relies on historical data and plotting points, Price Image is predictive and non-linear – making it much more useful in making strategic pricing decisions. It incorporates psychological elements, making it a consumer-specific metric.

A Nobel Prize-Winning Approach

The calculation of Price Image was inspired at Engage3 by Markowitz’s Efficient Frontier Theory. It’s a theory  that has been successfully used for decades in managing financial portfolios and is now applied to retail pricing.It enables retailers to strategically manage competitive price adjustments so they can balance their profit goals with a desired price image in the market.

Efficient Frontier

What to Look For in a Strategic Pricing Solution

Price Image takes psychological factors and applies them to pricing data. The resulting models can be used to predict future profitability and are not reliant on historical data. Below is a list of what to look for in a strategic pricing solution:

  • Integration with clean, comprehensive, and accurate competitive intelligence data
  • Statistically-driven performance reporting that separates real pricing impact from market level “noise”
  • Streamlined workflow for competitive price recommendations and approvals
  • Alerts for incomplete or outdated competitive data for review
  • A visual price modeling tool to define the impact of strategic pricing alternatives
  • Competitor activity and movement callouts on highly elastic products
  • Makes price recommendations based on your objectives for:
    • Price image
    • Profitability
  • Allows Merchants and Pricing Teams define their strategy and show the financial tradeoffs for different alternatives

The predictive model is especially valuable in forecasting sales, because Price Image allows a retailer to see how its customers are responding to different pricing strategies. Greater visibility translates to higher profit margins and happier customers!

Learn more about how the Efficient Frontier Theory is applied to retail pricing in this video.

10 Jan 2019
Earth Fare

CEO of Earth Fare Talks Shop With Ken Ouimet

At the inaugural GroceryShop event in Las Vegas late last year, Frank Scorpiniti, CEO of health and wellness store Earth Fare, sat down with Ken Ouimet, CEO of Engage3.

Frank talked about hiring a Chief Medical Officer for his stores, bringing more value to his health and wellness shoppers, and how he envisions a future of 1:1 customer-centric marketing using loyalty data in the very near future.

Following is their conversation:

Ken: Welcome, Frank, thanks for being here at the show with us today. What’d you think of the show?

Frank: The show’s been well organized, there’s an immense amount of emerging technology that really excites us for the potential to have it help Earth Fare continue to grow.

Ken: Is there any particular technology you’re most impressed with?

Frank: Well I spent some time on the exhibit floor and I was pretty impressed with what seems to be some off-the-shelf technologies to help us eventually create more attribute conversation with our customers, right on the sales shelf. And our customers are really seeking better health and wellness, so in order to tell a product story is something that we’re really looking forward to leveraging.

Ken: How would you communicate that to customers?

Frank: Well I think we have a lot of work to do to figure that out. That’s been a big challenge for us. As the leading grocer in North America with the cleanest product assortments, one of the biggest challenges we have is getting the message across to our customers about how unique our assortment really is, so I don’t have that solved yet.

Ken: One of the technologies that I was really impressed with was seeing the advances in the speech recognition.

Ken: At one end I saw something by Apple recently where it actually had a bot that could schedule a haircut for somebody, and get through all the navigation of a real conversation. I was curious to get your thoughts, as we get these digital assistants starting to have these capabilities that talk to people in real time, you see an opportunity where we could use technology to get back to the old store where the grocer knew the customer, and have a more intimate relationship with each consumer.

Frank: Why, I suppose that’s an opportunity, I think customers have a lot of questions in our stores. We have fantastic team members that, many of whom are lifestylers, they live the health and wellness lifestyle, but some of the questions are becoming more complicated about health, so the potential to have that kind of on-demand understanding and data could potentially create an experience for a customer that’s above what we can achieve today.

Ken: Yeah, I imagine as people become more aware of the foods they eat and the effects it has on their bodies, they’re getting more particular on what they eat.

Frank: Yes, consumers are starting to become very aware of the U.S. food supply and that over the years it’s had many, many more chemicals go into it. Some may say some of these products aren’t foods, maybe they’re stuffs with calories. We think that more Americans are looking for healthy foods to feed their family and feel good about what they’re doing.

Ken: I’ve seen a naturopath the last ten years and they routinely will take blood samples and test food sensitivity.

Frank: Yeah

Ken: And I was blown away when I asked them how many people were affected by food sensitivities, and he said it was roughly 70% is what they’re estimating, but only less than 5% are aware of it. There’s a lot of people out there that are affected but don’t know that they’re affected, and some of the athletes are starting to realize that they need to cut out the foods they’re sensitive to and their performance goes up. My brother has a doctor that, he has his office on top of a grocery store, and walks his customers through the aisles to show them what to eat. I’m just wondering, have you thought about having maybe even naturopaths. I know you have a medical officer, is that any direction you’re going?

Frank: We have a Chief Medical Officer, Dr. Angela Hind, and she keeps us on the cutting edge of making sure that we take out of our stores. We’re trying to keep away from things that make our customers sick, and she can only be in one place at one time. Some of the exciting stuff that I think is in our future, particularly with what you’re working on at Engage3, Ken, is our ability to take our loyalty data, where our customers share with us some of their needs around health, and be able to customer-centrically create one-to-one offers. And maybe that could take the place of the naturopath, probably not all the way to the extent your brother experiences or having a naturopath above a store, but the opportunity to guide a particular person with food sensitivities into things that are safe for them, say through an app that [ Earth Fare ] eventually could offer our customers, that could be an incredible experience that I don’t see happening today.

Ken: Yeah, I think there’s a real need for that, because you start looking at reading the labels for what fits your diet, that’s a lot of work. I would think as a consumer I would want something that navigates me around the store like the GPS navigates me around the city.

Frank: I think that could be just an incredible advancement in retail for [ Earth Fare ], we have a food philosophy that disallows a lot of artificial ingredients, and so we say to our customers, “We read the labels so you don’t have to.” That’s removing a lot of the chemicals, but to take it to the next level that you’re describing, then tailor the shop for each individual consumer, it really could excite our customer base. And they’re already looking for better health so it’s the right audience.

===end===

Engage3 Competitive Intelligence Platform helps retailers like Earth Fare improve their pricing performance and compete more profitably through data science & analytics. To learn more about voice-activated shopping and other innovations discussed at GroceryShop, watch this video of Tim Ouimet discussing the rise of agent-based shopping.

08 Jan 2019
Gartner

Gartner’s Market Guide for Unified Price, Promotion and Markdown Optimization Applications, Update 2018

Now more than ever, pricing based on solid data is necessary for retailers to succeed in this increasingly competitive market. This latest report from Gartner gives an overview of the different levels of pricing automation, and finds that most optimization service providers aren’t keeping up with the needs of retailers.

Gartner Curve
Tiers of Integrated Price Optimization by Gartner

Unlike most vendors in the space, Engage3 has developed a platform capable of bridging the gap between pricing models and algorithmically-driven pricing. Uniquely, Engage3 starts with the cleanest competitive data available, making sure that your optimizations are based on a solid foundation. Check out our cross-channel Competitive Intelligence Platform offering here.

We also combine decades of expertise in retail pricing with strategic insights made possible through data science. Our Competitive Price Response lets you manage your price image goals vis-a-vis your profitability goals. For more information on the theory of Efficient Frontier, the science behind our optimization schemes, watch the video here.

You can find the rest of Gartner’s report and their review of Engage3’s offerings here.

To learn more about how Engage3 leverages big data and machine learning in the UPPMO landscape, request our White Paper here.

18 Dec 2018

The Aldi Effect: Are Walmart prices higher in locations where there is no Aldi store?

When European retailer Aldi started opening stores up and down Britain in 2016, people who lived close to a new retailer location started noticing that the value of their homes went up by as much as £5,000. It was called the “Aldi Effect” by the local media and, soon enough, the vicinity of an Aldi store to a piece of property became a listing feature.

Aldi started putting up more stores all over the U.S. starting in 2011, with a total of 1,600 stores to date. And just like in the U.K., it would seem that there is yet another advantage to having an Aldi store in your neighborhood – lower prices for everyday groceries at your local Walmart store.

Walmart and their everyday low price (EDLP) approach has consistently driven a low price image across the U.S. With their limited assortment and private label focus, Aldi has also worked to deliver customer value through low prices. When both retailers are present in a market, they have demonstrated an ability to fight head-to-head for low-price leadership.

Engage3 collects and monitors grocery pricing in markets across the U.S., and identifies pricing patterns and market trends.

For this study, we created a basket of 50 grocery staples that were price checked at three Walmart locations within each of the four Texas markets studied – Austin, Dallas-Fort Worth, Houston, and San Antonio. Dallas and Houston have 36 and 50 Aldi store locations, respectively, while Austin only has 1 store location and San Antonio has none. The competitive landscape in Dallas-Fort Worth and Houston is much more robust, with not only Aldi in the mix, but Kroger and Safeway banners as well.

Our study revealed that in Austin where there is only 1 Aldi store location (north in Pflugerville), Walmart pricing for the basket of staples was 16.2% higher than in Dallas, and 17.6% higher than it was in Houston.

Aldi Report Austin

In San Antonio where Aldi has no store presence and where H-E-B and Walmart are the dominant grocery players, we found that the Walmart basket was between 21% and 22% higher than the exact basket in Dallas-Fort Worth and Houston, respectively.

Aldi Report San Antonio

 

While the average pricing differences in the four cities taken together were between 6% and 11%, some pricing disparity on items like peanut butter and mac and cheese were fairly significant. The chart below shows peanut butter at a Walmart store in Dallas-Fort Worth priced at $1.18, while the same jar was priced at $2.18 in Austin – a whopping 54% difference. Similarly, the mac and cheese, priced in the Dallas-Fort Worth stores at $0.34, was double the price at $0.68 each in Austin.

Aldi Report Table Austin DFW

The same pattern can be seen in Houston, where there are currently 50 Aldi stores. The chart below shows peanut butter at a Walmart store in Houston priced at $1.78, while the same jar was priced at $2.58 in San Antonio, or 45% more. The same mac and cheese, priced in the San Antonio store at $0.68, is 100% more expensive than in Houston at $0.34.


The market basket data used in this analysis is objective and precise. But while the same 50 items were used across all markets, the correlation of Aldi’s effect on a market is still subjective.  Based on Engage3’s observations of competitive pricing data across the U.S., we have determined consistent patterns of Aldi’s influence and effect on market pricing.

Pricing has always been like a chess game, where each retailer is reacting to their competitor’s moves, while trying to predict how their competitor will react to their maneuvers.  But, unlike chess, this game is often played with 3 or more players, and aggressive moves can make it difficult to discern strategy from reactive tactics.

For more information on how to build a strategic competitor assessment and market price monitoring program, watch our competitive pricing video here,  request our white paper on how to leverage AI and big data in competitive pricing here, or contact us at 530-231-5485.

 

 

05 Dec 2018
Agent-based Shopping

The Rise of Agent-based Shopping

 

Retail is at a tipping point

This was a main theme at GroceryShop’s inaugural event last month in Las Vegas. The event was attended by over 2,200 retail and CPG executives and was billed as the industry’s leading event for innovation.

Opinions about the tipping point were punctuated by Nielsen’s prediction: in 5-7 years, as many as 70% of U.S. consumers will regularly purchase consumer packaged goods online (“Digitally Engaged Food Shopper”). By 2022, they speculated consumers could spend $100 billion per year for online groceries (equal to $850/year/household).

For shoppers, digitization lowers barriers, making it easy to source product, compare buying options, find offers, transact, and take possession. For retailers, this means further downward pressure on price as competition evolves across more market segments than ever before: store, product, time, customer, channel, pickup and delivery options, cross-sell alliances, marketplaces and shopping apps.

 

Direct to consumer

Another big topic at the show was brands going Direct To Consumer (DTC) via Instacart, Amazon, and other platforms. For shoppers, it’s only getting easier as computers and AI get better at sourcing, comparing, and finding buying options that best meet a shopper’s current need. In this digital future, relevant offers will find a shopper based on her context (location, preferences, urgency, etc.). Margins will follow a retailer’s ability to make its assortment, offers, and delivery hyper-relevant to a shopper’s context.

 

Artificial Intelligence

Innovative retailers are leveraging AI to defend margins by segmenting markets better and by personalizing services and offers. In her talk, Google’s Laura Antonolli demonstrated Google’s AI-driven conversational assistant, in a machine-to-human interaction. Traditionally, a sales assistant’s role is to connect, understand, personalize and serve. In Laura’s demonstration, Google’s AI assistant searched for a hair salon, called to coordinate calendars for an appointment, and selected a haircut from an array of services.

 

Agent-based shopping

We are witnessing the rise of a new paradigm in retail – agent-based shopping. Laura said shopping agents and voice-activated search are a new battleground, stating that 22% of Google’s mobile search is voice. Forrester Research Analyst George Lawrie reported that “digital is no longer just a marketing channel, it’s now a sales channel.”

In one retail use-case, George shared that Alexa users spent, on average, £8 (eight British pounds) more per basket than at Morrisons. As of today, use cases for digital agents and household consumables are limited. That said, the promise ahead is for agents to create hyper-relevant offers and close sales based on an individual shopper’s context, values, and preferences.

 

Demand-side attributes

In large part, limitations come from the need to understand how shoppers compare substitutable product offerings and how those comparisons change under different pricing and offer scenarios. This applies to both within and beyond a retailer’s four walls. As an industry, we’re really good at supply-side product attribute data (i.e. weight, size & ordering info.). But we have yet to understand product attributes on the demand-side. Whether online or in-store, the old adage “price drives sales like no other factor” still holds true. From that perspective alone, comparability of pricing and offers within a category and across the marketplace are significant dimensions of demand-side attributes.

Comparability lies at the heart of understanding shopper values and preferences. As such, this represents a central value driver in any automated shopper feedback system. Without comparability information, offer personalization is largely blind to a shopper’s context, i.e., blind offers are not relevant.

 

Data takes a new turn

This brings me to a second take-away from the event. We are witnessing a fast acceleration in the variety of demand-side data elements offered by vendors in the space. At GroceryShop, these companies included: Engage3 (my company), Nielsen, Gladson, 1010data, EnterWorks, Label Insights and many more. Each of these companies offer unique data elements relating to different and new demand-side attributes.

As an example, Engage3 provides store-specific comparable pricing data. Nielsen provides measurement data aligned with many causal data elements. Label Insights provides detailed on-package attribute, ingredient and claim data. Data sharing and data feed integration between data vendors is also accelerating. These sharing and integration relationships open new paths to support the full promise of agent-based retailing.

Given the importance of product comparability, expect comparability to emerge as a primary focal point for integration. At Engage3, these sharing and integration relationships are beginning to yield new benefits, including:

All of this helps retailers automate and increase ROI from their pricing, offer generation, segmentation and personalization efforts.

In his talk, Earth Fare’s CEO, Frank Scorpiniti, spoke about AI as an “invisible advantage” that “removes repetition.” He reported that price promo and promo cadence all together yielded ROI of 300 basis points (3% of sales).” Adding “automation requires data quality” and that Engage3’s data has “near 100% accuracy.”

Getting data trustable is one step. Preparing integrated data for automation & advanced analytics is a step beyond. Supporting a client often means integrating a variety of data feeds from across a client organization with that of multiple data vendors. And building those feeds into a model is crucial so decisions can be automated in a controlled way.

Adding to the momentum, research dollars are beginning to flow as universities define research priorities in this space. One university we spoke with plans to create a center for excellence in food through the integration of personalized health, nutrition, and sustainability. Their effort would align both industry executives and academics from the business, engineering, supply chain, medicine & nutrition schools.

Agent-based shopping is set to emerge as a new battleground. Retailers that are positioned to make use of these new data feeds will climb the evolutionary path faster. Expect the industry to evolve rapidly in support of agent-based shopping.  It’s an amazing time to be in retail!

For more information on competitive pricing, go to our blog “What to look for in a competitive pricing platform.”

 

 

30 Nov 2018
Tariffs

Pricing in a Post-Tariff Market

Pricing in a Post-Tariff Market

As the markets closed on September 17th, the United States announced another round of tariffs against Chinese products. The tariffs, this time consisting of $200 billion worth of goods, were implemented on the 24th and will increase from 10% to 25% over the coming months. In return, China fired back with a list of 5,207 U.S. imports to be taxed, totaling $60 billion. National retailers like Walmart have responded by voicing concerns to US Trade Representative Robert Lighthizer and addressing potential costs to American consumers (CNN).

What started as a way of bolstering American business has become an all-out trade war between the two countries, with retailers in the crossfire. In such a situation, it can be difficult for affected retailers to implement new strategies quickly and effectively. Thankfully, with some insights into their competition and the national price leader, the most prepared retailers can come out on top.

 

Effects on Price Image

The prime question is this: who is going to pass on the cost to consumers first? Every retailer in the nation is waiting with bated breath for the answer. Private letters from Walmart and Target, among many others, have hinted at increased costs on the horizon, but there is no certainty of the first retailers to implement them (CNBC). The issue is that whoever passes the cost first hurts their price image the most. Items that were not hit by tariffs may still drop in sales because of the price adjustment, making the threat far greater than anticipated.

Still, this is only the beginning. The first retailer experiences the largest effects of the tariffs, but the next retailers to pass on the cost to consumers are also affected. This is where real-time competitive data can make a difference. Imagine that competing Store A raises the cost of a certain tinfoil to $8 in a market, and you are able to monitor that increase. From there, you can raise the price on that same product at your store to a lower price point than Store A. Though both products are affected by the tariff, your price image for tinfoil is maximized because 1) you were not the first in the market to raise the cost and 2) you are selling that product at a lower price than Store A.

 

Sliding Scale Tariffs

What makes these observations more crucial is the nature of the tariffs themselves. The increased cost for the latest affected products will go from 10% to 25% by January 1st, 2019, meaning that these small-scale retail battles will be happening on a weekly or even daily basis. Having up-to-date information on your competitors—both on a local and national scale—will translate to more victories.

The reality is that most retailers will face losses in the coming months because of tariffs, and stores hit especially hard by the increases have already taken steps to address them (USA Today). Accurate and timely competitive data can help to mitigate losses, especially when monitoring the national price leader. This is where store-level pricing is most important, because some price zones will be more heavily affected than others. Competitive data can inform a retailer when their competition is responding to tariff costs and how they can respond effectively. Implementing enterprise-level decisions in stores and going down to the local level can translate to a significant competitive edge in a post-tariff market.

 

A Watchful Eye

With the tariffs increasing to 25% by the end of the year, the market is racing to recover losses—the earlier a retailer can adopt a competitive strategy, the better. Because most retailers operate on low profit margins per item, an increase of even 10% on a product adds up quickly. In the case of a KVI, the increased cost to the retailer could negate any profit on that item, or even come at a loss. Figuring out a competitor’s pricing strategy and how often they update prices makes for valuable insights for decision-making.

At any point in the timeline, a strong price image is necessary to drive traffic to your stores. As we get further into the year, keeping an eye on the local effects of tariffs will be as important as pricing on a national level, and accurate competitive data can make all the difference. With the right insights, the tariffs present a unique opportunity for retailers in the coming months. Click here to learn more about Engage3’s automated price monitoring and register to receive information.

25 Oct 2018
KVI and Price Image

Known Value Items – Drivers of Price Image

A Shopper’s Store-switching Decision

A KVI is a known value item. It’s an item that disproportionally drives the price value perception. So, in a grocery store it would include eggs and an automotive store might include motor oil, and a convenience store it might include cigarettes.

The reason that KVIs are important is because they drive a shopper’s store switching decisions. If the retailer’s prices are out of alignment with the prices that shoppers remembered, then the shopper can reevaluate their decision to shop with that retailer.

A question you can ask a shopper is, what items do you stock up on? And at what price points do you stock up? And you’ll begin to understand what a KVI is with the answers you get to that question.

A Tiny Number of Items

Another element that’s really important with the known value items is that it’s a very tiny number of items that drive a retailer’s perception in the marketplace. Typically, about a third of the price perception comes from only two-and-a-half percent of the products. It’s a very concentrated number of items, and this holds true across grocery, drug, mass,convenience, pet, auto—virtually all retail sectors. So, getting it right is critical.

Dynamic KVIs

Traditionally, retailers will evaluate their KVIs once a year. Over time it’s gotten to a more periodic basis where they’re doing it more often, but the market’s changing faster today than it’s ever changed before. Things are getting localized, things are getting personalized, and with that the shopper’s price perceptions are being set more dynamically.

All of these things mean that calculating KVIs based at the enterprise level is the wrong way to do it. The analysis needs to come down to the store level, down to the shopper level, down to the daily level, and have items coming in and out of the KVI list at those lower levels.

Increased Complexity

The challenge is that all this results in a lot more complexity that needs to be managed. The comp shop programs that were easy for one person to manage before now explodes the amount of competitive data that’s needed and the amount of management time that’s required.

A Platform to Manage Margins and Price Image

The retail marketplace is only going to get more competitive, and retailers need a platform to support themselves in this new environment. At Engage3, we’re on a journey to build that platform to enable the retailer – the early adopters – to outpace their competition so they can outperform them in terms of Margin and Price Image.

13 Sep 2018

Price Optimization 2.0: The Efficient Frontier in Strategic Pricing

When managing a financial portfolio, you’ll need to determine how much to invest in each asset. If you have a thousand assets, it becomes a very complicated decision on how much to invest into each one. Harry Markowitz’s Nobel Prize Winning portfolio management theory, called the Efficient Frontier,  allows investors to boil this problem down into a strategic decision of how much risk to take for a given return.

In retail, you’re managing a portfolio of products. Instead of an investment decision, however, it is a pricing decision of how much you will be investing into each product to lower the price. The Efficient Frontier allows us to boil that pricing decision down into 2 dimensions – Price Image and Profit Goals. We use this tradeoff in retail pricing – where you have to manage thousands of pricing decisions to achieve your desired return. The question is: How do you roll that up into a strategic decision?

Because changes in retail pricing are becoming faster, more localized, and being split across different channels, we knew that we needed a tool to pull all that together and manage a consistent strategy across different price types. It turns out that the Efficient Frontier theory is the most powerful tool to solve this complex problem.

If we apply the Efficient Frontier theory to retail product pricing, then the dimensions we’re considering are the Price Image along the X-axis and the Profit Goals along the Y-axis. The highest point of the curve is where you make the most profits. Those are short-term profits. We then get the point-of-sale data that’s recording short-term decisions from customers, and that’s what the demand models are modeling.

There is a risk associated with pricing at the top of the curve because while that is where you make the most short-term profits, it’s also where you’re burning your Price Image. At this price point,the customers aren’t going to come back. The strategic decision to make, therefore, is how far you have to go down and how much you have to invest into having a lower Price Image. The decision is unique to each retailer and each strategy. It’s even unique to each category, fulfillment type, or each channel that you’re pricing.

There is a lot of information and power that goes into creating one of these Efficient Frontier curves. To illustrate: imagine that you have just two products, and each product has ten possible price points. If you look at all the possible ways to price those two products, you’re going to make a grid of prices, and it’s going to be a 10×10 grid. That’s a hundred different price points you’ll need to evaluate for just two products. If we add a third product and it has another ten price points, it’s now a cube and there are a thousand elements in that cube. The growth is exponential–you add a fourth product and there are ten thousand elements. What happens when you have a category of a thousand items? You will now have just one store, one category, with a thousand items. The number of pricing scenarios that need to be evaluated is now ten to the thousandth power. That’s more atoms than there are in the universe!

These are huge computational problems, and this is where algorithms become important—algorithm scalability is extremely important in these optimizations. To manage a hundred million prices in a dynamic market is a really complex undertaking. How do you boil that down to something you understand and make a strategy around? The Efficient Frontier is a tool that can collapse all those decisions into strategic decisions where someone, like an executive, can get their head around. It enables that executive to integrate the strategy all the way to the tactical execution, while automating those decisions.

This is what is exciting about price optimization problems. The same models that were created for investment portfolios are applicable to retail situations, and they allow you to make pricing decisions confidently–even in the face of 10 to the thousandth power price scenarios.

25 Jul 2018
Retail Predictions

Ken Ouimet’s 5 Big Predictions for the Retail Industry

Engage3 is working to create the ultimate platform for retailers to monitor and develop pricing strategies. Even when focused on products at the store and item level, changes in the market influence these strategies significantly. I met with our CEO, Ken Ouimet, in front of the beautiful Mondavi Center in Davis, California. With big changes at Amazon and Walmart this past year, I asked him to describe the future that he sees for the retail industry.

Gartner identified Ken as one of the pioneers in the retail pricing optimization space. In this video, he shares his insights and enthusiasm for what’s ahead. You can also watch the video here.

 

 

15 May 2018
COO

Engage3 COO Edris Bemanian Talks Pricing Strategy, Pressures, and the Market

Last month, Robert Schaulis of Andnowuknow interviewed Engage3 COO Edris Bemanian on his observations of pricing pressures from the likes of Amazon and Lidl. “The biggest trend is that pricing and assortments are becoming more dynamic and localized,” Edris says.  He notes that e-commerce is now becoming a fundamental part of retailers’ strategies versus just a “me too” approach. Read the full article in Andnowuknow.com.