Category: Pricing Strategies

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:

  • More trustable competitive pricing and product comparability data
  • More precise methods for measuring price image
  • A broader and more frequent census of the competitive market
  • Deeper insights into strategic and tactical pricing dynamics
  • Improved automation and control over strategic pricing

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!

 

 

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
Ken Ouimet Efficient Frontier Theory

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.

14 May 2018
pricing

White Paper: Leveraging Big Data and AI in Competitive Pricing

Big data and Artificial Intelligence (AI) are giving rise to new retail pricing strategies that were not possible just two years ago. The explosion of data available has provided the perfect storm for AI to thrive. Retailers are starting to differentiate themselves like hedge funds with high-speed pricing models and proprietary market data.

Find out how you can use accurate, localized competitive data and pricing analytics to execute your business strategies today. Register to download the white paper now.

26 Mar 2018
MissionControl_Competitive Pricing Platform

What to Look for in a Competitive Pricing Platform

What to Look for in a Competitive Pricing Platform

Precise and Accurate Data

First and foremost, a competitive pricing platform must have the ability to collect precise and accurate pricing data. This allows retailers to target competitive shops, optimize frequency, and specify which items to focus on within regions or individual stores.

Rather than casting a wide net to see what useful data gets brought in, retailers must be able to get a global look at the actions of their competitors while also drilling down to store-specific opportunities. When they have both views, they can see clearly where they are winning and losing. Essentially, such a system puts both a telescope and a microscope into the hands of merchants and their pricing analysts, enabling them to comprehensively study their competitor’s universe. It allows them to reverse-engineer their competitor’s approach to pricing and to develop a targeted response, especially if they see a weakness.

Quality Assurance Workflow

Real-time_QA_Competive Data collection
A strong quality assurance workflow ensures that data being collected is accurate.

A competitive pricing platform must also have a strong quality assurance workflow. With today’s mobile app-enabled technology, automated processes can greatly reduce manual errors and ensure that only quality data is being captured at shelf edge. Additionally, such apps can compare shelf data against historical records, flagging any SKU pricing that seems historically unreasonable. Advanced analytics can assure that the data being captured is accurate in terms of price, brand, sizing, and product attributes. This technology can eliminate much of the human error that has plagued competitive shop programs.

Product Attributes

With the rise of private labels, competitive pricing platforms must be able to compare product attributes. In traditional competitive shop programs, as many as 40% of items go unaccounted for because there is no UPC match. To solve this problem, competitive pricing platforms must be able to utilize visual data capture technology and advanced character recognition to compare product attributes. This allows product linking to occur not just by UPC, but also by key attributes and statement of ingredient similarities, i.e. gluten-free and organic. This creates a more accurate picture of a competitor’s private label pricing strategy and their total value proposition.

Customized KVI Lists Based on Statistical Analysis

MissionControl_Competitive Pricing Platform
Dynamic KVI list support can help you customize by store.

Historically, cost and timeliness have made it difficult to acquire quality competitive data. Given the dynamic nature of the retail environment, static KVI lists are not responsive enough to the realities of where to focus competitive pricing efforts across various geographies and store-specific categories. The retailer needs a pricing platform that allows them to shift from static KVI lists to ones that are easily customized by banner or even by specific store. Rather than taking a blanket approach, the critical decisions of where, what and when to comp shop should be based on strategic statistical analysis.

Drill-Down Capabilities

Merchants need the ability to drill down and understand the decisions competitors are making within specific regions, designated market areas (DMAs), cities and individual stores across their overall pricing strategy or within specific merchandise categories. This would enable merchants to lead their competition by being right on pricing with the right items that are important to customers at a localized level. Such flexibility in designing and executing a more targeted approach to competitor pricing would allow for significant savings in budgeted dollars for competitive shops. A retailer could go after the data they actually need when they need it, rather than spending dollars on costly full book programs.  

Correlating Online and In-store Pricing

In today’s world of e-commerce, more and more retailers are taking an omni-channel approach to selling. A technology-enabled competitive pricing platform needs to take advantage of advanced web crawling algorithms to acquire this competitive data and correlate it against the data captured by auditors in physical store checks. This would enable a more efficient and cost-effective approach to acquiring competitive pricing data.

Aligning Objectives

As advanced analytics enable faster and more accurate decision-making, organizations will need to change to more cross-functionally aligned metrics that strategically drive the financial success of a company. When considering today’s retail organizational structure, is what drives a merchant’s decisions the same as what motivates the employees in a pricing department? Having the data to make decisions regarding competitive pricing at the speed of retail requires a major step forward in enabling accurate pricing decisions to be made with a sense of urgency and strategic intent. However, to fully unlock its true impact to P&L, the retailer will benefit from progressive thinking around how to align objectives and an incentive structure that motivates and drives collaboration. This will enable different departments with complementary skill sets to pull the rope in the same direction and drive a total value proposition focused on the customer.

 

22 Jan 2018
Thumb1

The 7 Challenges of Modern Competitive Pricing

Strategic pricing is at the heart of retail competition. It has famously driven the business decisions of Amazon, Walmart, Lidl and Aldi that we see all over the news. But in order to develop more effective pricing strategies, retailers need a different approach to competitive pricing, one that addresses the historical challenges of competitive shop programs:

Problem 1: Low Completion and High Data Error Rates in Competitive Pricing Shops

Data capture has always been a labor-intensive, error-prone process. Price checkers match wrong items, capture the wrong price points (e.g. promotional vs. everyday retail) and encounter a variety of other issues. With quality assurance happening on the back end of the price-checking process, incorrect matches have the potential to pass through the system downstream to the retailer.

Problem 2: Like-product Comparison

Different assortment sizes and formulations pose challenges to price checkers who work from static comparison lists. With Amazon’s rapidly expanding penetration of the food retail market, center-store items are becoming more and more commoditized with price having a greater impact on consumer decisions. At the same time, specialty formats like Trader Joe’s and deep discounters such as Aldi and Lidl continue to execute on delivering cost-effective differentiated private label programs. The fresh side of the store is becoming the battleground where stores need to differentiate themselves. In order to do so, accurate competitive pricing programs that take into account size, quantity, formulations, and other attributes.

Problem 3: Lack of an Integrated Omni-channel Approach

As traditional retailers move further into e-commerce and online advertising, their approach to competitive pricing has, for the most part, remained a manual process, limited by the amount of labor resources to physically shop competitor markets. By using technology to automate competitive shops, they can deploy more labor to focus on unique assortments and integrate online and in-store activities. This creates a more comprehensive picture of competitor pricing strategies.

Problem 4: Static Lists, a One-Size-Fits-All Approach

Often, retail companies rely on lists of Key Value Items (KVI’s) to drive both their competitive shop programs and their pricing strategies. These lists are usually static and don’t take into account differences across competitors and their diverse locations. This approach can be extremely inefficient as auditors go to stores looking for items that may not be part of that specific store’s assortment. When this happens month after month, it quickly becomes costly.

Problem 5: Tactical, Not Strategic

It’s easy to fall into the trap of using competitive pricing programs to fill tactical rather than strategy needs. Competitive pricing programs should be used to understand not just the competitor’s price on individual SKUs but also their total pricing strategy across their footprint. With consistent, accurate and real-time data, a retailer has the ability to look at trends within the marketplace, understand the actions of competitors, and use predictive analytics to ensure that their value proposition remains relevant to the customer.

Problem 6: Expensive: Throwing Money Away on Full Book Shops

In order to gain a comprehensive view of a competitor’s pricing, competitive shop programs often focus on a large number of items and numerous stores. This is due in part to the challenges mentioned above regarding data accuracy and reliability of the manual process. To increase reliability, retailers often increase labor by checking more items in more stores or increasing the frequency of checks. This is expensive. The top 10% of products sold typically represent 50% of the total sales dollars. Therefore, full book programs that invest as much in competitive shopping slow-moving items as in fast-moving products are not cost-effective.

Problem 7: Wrong Measures and Incentives

A major internal challenge for the retailer can be its organizational design and HR support. People are fundamentally motivated based on how they are rewarded. However, merchants and pricing departments may be measured against completely different success criteria that but also work against each other. For example, when Pricing strives to maintain a company’s value proposition by driving towards a CPI index, this may run counter to the gross profit targets set by merchants. Progressive merchant leaders, with the support of HR, need to bring these departments together with aligned KPIs and metrics. Driving EBITDA should be everyone’s goal. Organizational structures and compensation schemes should encourage productive and aligned behaviors.

Coming Soon

We’ll show you what to look for in a competitive pricing platform in our next blog. Stay tuned!

28 Apr 2017
pricewar

“Surviving the Emerging Price War” Insights

Industry-expert and Chief Architect of Brick Meets Click, Bill Bishop, hosted a highly-anticipated webinar session with Engage3 CEO Ken Ouimet and COO Edris Bemanian. “Surviving the Emerging Price War” provides in-depth insights, tangible examples and tips and tricks on how to compete effectively in the face of a brutal and imminent price war among retailer powerhouses. The webinar supplies all of the key ingredients in making up a retailer’s survival toolkit.

“When elephants start to dance, mice get trampled.” Ouimet began the webinar with an analogy that accurately reflects the current state of affairs in the retail industry prior to highlighting Amazon, Aldi, Lidl, and Walmart’s price commitments in the emerging price war. As these giants begin investing in their pricing, the “mice” that are forced to follow but fail to react strategically remain in the elephants’ path.

Ouimet continues with a five-step plan on how to survive in the face of a price war and be met with some form of success or resilience. His ideas center around the notion that “the best offense is a good defense.”

Understand your customer’s perspective.

Using competitive intelligence data shouldn’t be the only tool retailers leverage. Retailers must identify which items are most important to their local customers and understand what items they are comparing against at their competitors’ stores. It’s essential to utilize accurate product linking practices to compare products in the way that customers do with attributes.

By understanding the way customers value their products and perceive the changes retailers make to their pricing, retailers will unlock opportunities to move their customers up the loyalty ladder. Engage3 is collaborating with customers to bridge sales, market share, customer survey, and competitive intelligence data to identify the items that are most relevant to their customers in each market and refine retailers’ KVI lists to reflect this.

Gain visibility into your local competition.

Slide0.JPG

If retailers don’t have visibility into local competition, then they simply can’t compete. Convenience stores have a high level of what Engage3 calls “localization” (geo-specific pricing), and drug stores have a lower level of localization. However, as a time-series analysis shows, localization scores have been increasing, and retailers like Safeway, Kroger, and Publix are developing higher levels of localization. Kroger, especially, has been met with a high level of success with localized assortments.

If competitors are not very localized, it provides an opportunity to strike hard and fast without any visibility. Engage3’s platform, in particular, takes price change frequency and competitor assortment localization into account when improving competitive intelligence programs over time.

Fly under the radar and attack where they aren’t looking.

Slide2.JPGOne suggested tactic could be moving away from larger competitive zones and instead into micro-zones. A regional grocery retailer that scores very highly with consumers in regard to their price reputation was able to maintain their positive reputation by leveraging their smaller zones to take advantage of their competitors’ blind spots through a mix of lower prices to earn price reputation points while taking higher margin on other items by allocating across zones. Engage3’s Competitor Strategy Analytics reverse-engineers retailers’ pricing and assortment strategies to identify margin opportunities and competitors’ price zones.

Strike hard and fast.

It’s not enough for retailers to Slide1.JPGattack from hidden angles, but they must also have an element of speed behind them. Amazon has a high price change frequency on several items found in conventional grocery stores, and the juggernaut’s price change algorithms are highly responsive. Retailers are taking notice of Amazon’s practices and efficient strategies and are beginning to follow suit.

Retailers need to minimize the time it takes to respond to margin opportunities or price reputation risks by getting data that is as fresh as possible to maintain visibility. Engage3 has helped customers identify when retailers can confidently leverage online data to provide a faster signal to increase visibility and proactively identify opportunities.

Reinvest benefits to defend your turf.

The environment of a price war is pressing and inevitable, so the first step to surviving is determining how to invest optimally in your respective markets by efficiently monitoring the local competition. Once retailers can establish a robust process in a program, they should be able to reinvest those savings to identify additional margin or price opportunities.

Personalization

The segment concluded with a last, but certainly important, strategic lever in fighting a price war: personalization. Ouimet believes that the future is personal and that personalization is unique in the way that it’s a highly desirable tool for consumers that also helps create a tighter relationship within retail communities. It provides more loyalty and more convenience for the consumer, and when applied to pricing, it becomes the ultimate segmentation and the most powerful means to “fly under the radar.”

The five-step plan is heavily reliant on updating competitive shop programs and price optimization strategies. According to Ouimet, those retailers seeking to constantly improve will be well prepared if there is a price war.

To register to watch the full webinar and find out more invaluable insights, click here.