Author: Accelerated Analytics

Not To Be Outdone, Walmart Presses Into Prestige Beauty

Walmart announced its partnership with British beauty retailer Space NK which was founded in 1991. The partnership will be seen across 250 stores and DOTCOM in a collaboration they’ve called BeautySpaceNK. Beginning last month, Walmart’s website began featuring over 600 Space NK haircare, makeup, skincare, and bath and body products across several price-points. Some brands will remain exclusive to Walmart. With this delve into luxury, indie, and exclusive lines at select Walmart stores, box retailers are becoming increasingly competitive throughout the beauty space. Learn more about our prestige retail reporting enhancement, such as our dedicated Ulta Reports here. Then, let’s set up a meet to look over your brand’s use of its available data and how our sales reporting tools can help your brand specifically stay ahead of the curve at box stores like Walmart and Ulta.

Predictive Analytics and Machine Learning: No, they’re not the same thing

By now, most companies know that data is an indescribably valuable resource for supporting smart decision-making and enhancements in business operations. As data, and its uses, continue to evolve, a growing number of businesses are embracing predictive analytics to expand data’s benefits on a massive scale.

Predictive Analytics = Machine Learning?

In short, no. Although they work hand-in-hand, predictive analytics and machine learning are not exactly the same thing. Let me explain.

Recommended for you Machine learning is defined as a subset of artificial intelligence in which processes are automated by using sample data and pattern recognition to enable systems to carry out tasks without being specifically programmed to do so. Machine learning uses algorithms to build models to make predictions without the need for human supervision. These algorithms are used in many automated tasks, such as email filtering and network security, and uses iterative processes to continue to learn and independently adapt when provided with new data. It’s not a new concept by any means, but it is one that has been refreshed, evolved and become more useful than we could have imagined only two decades ago. Your shopping suggestions, based on what you’ve looked at or bought before? Targeted ads? Your Netflix and Pandora feeds? They’ve all been developed through machine learning, using the input from you to learn your patterns and preferences in order to accurately recommend products, services and entertainment tailored to you

Peer into the crystal ball Machine learning resides underneath the umbrella that is predictive analytics, which, along with other statistical techniques, such as data mining, and uses established patterns to identify likely future outcomes. The predicted outcomes could include consumer behaviors, market fluctuations, credit worthiness and more. Predictive analysis is used in industries across the board, from marketing to insurance, telecommunications to credit score calculation, even healthcare.

So, predictive analytics, as more of a concept than an operation, predicts outcomes based on historical statistical data while machine learning is a process – the result of evolution in pattern recognition. The models which are created eventually ‘learn’ to make accurate decisions backed by the algorithmic data it processes.

Predictive analysis software solutions use built-in algorithms to create predictive models. The algorithms – classifiers – indicate what categories the data belongs to.

The most commonly-used predictive models are neural networks, decision trees and logistic regression. Modeled after the the human brain’s neurological processes, neural networks are used to solve complicated patterns and are extremely helpful in analytics involving large data sets. They are able to decipher nonlinear relationships, even if some of the variables are unknown. Decision trees are produced by algorithms to analyze data by grouping it into branch-like subsets based on input variables, effectively tracing the path of ‘thought’ leading to a decision. Regression analysis works to identify patterns and relationships in large, diverse sets of data.

Less-common classification algorithms include time series analysis – a series of data points indexed in time order; cluster analysis – grouping like variables together; and outlier detection (also known as anomaly detection). Furthermore, algorithms can be used together to achieve better predictions than by using one lone algorithm; these combined algorithms are called ensemble models.

These unique classifiers approach data in different ways, so to get the needed results, the right classifiers need to be put into use.

How does predictive analysis help you win at retail?

No matter how much data an organization generates, if it can’t be properly utilized, that data is rendered useless as an untapped resource.

Enter EDI 852 Your EDI 852 data can tell you a lot about your business. Some insights provided by your EDI 852 include:

Items out of stock, almost out of stock, or overstock, measured in units on hand. By isolating each of your items at a store level and applying filtering for your desired min/max inventory position, you can quickly determine an average units sold during a specified time frame, then use this to calculate inventory weeks (or days) supply on-hand. Supply on-hand is a predictive indicator that will identify trends and alert you to take action if/when needed.

Top- and bottom-selling items. Obviously this is measured in units sold. Identifying top items at a store-by-store level over time will uncover trends in consumer behavior and preferences that are helpful in knowing what items to continue (or discontinue) carrying and at what price points the items sell the best/worst. These predictions will help you make smart decisions regarding ordering, stocking, scheduling, plan-o-grams, and more factors that affect your bottom line.

Period-over-period and regional comparisons. Comparing sales and inventory for similar periods of time and by geographic region will help you adjust your inventory min/max. Using algorithmic predictions, your analytic software can automate some, if not all, of these processes.

Most EDI 852 data arrives with very basic measures for units on-hand and units sold. By creating the right ensemble models of algorithms, analytic solutions can do the EDI 852 translation, database storage and number crunching, meaning your focus can remain on growing your team and improving your bottom line.

5 Ways to Increase your Sales in 2019

Increase Sales

Photo by Mike Petrucci

Retail can be a volatile space – at times, it’s a feast-or-famine situation. Many times, a sharp decrease in sales are due to factors outside of human control such as bad weather, product recall, new competition, changing consumer preferences, etc., but there are plenty of ways to combat the bottom-line-eating “slump” in sales.

Your business exists to provide goods and services to your customers as well as, of course, growing your ROI. Knowing how competitive the retail sector is, you must be thick-skinned to successfully grow a business in this cutthroat industry.

But you also have to be innovative.

Consider the following actions that, done right, will boost your sales, customer base and ultimately your ROI.

POS Data Analysis

Photo by Stephen Dawson

Analyze your POS data

These reports help you identify changing consumer preferences and new trends
Consumers can be fickle. Here today, gone tomorrow, taking their dollars with them. You have to be able to keep up with these changes and act quickly to shore up any cracks that begin showing. Keeping up with ever-changing landscapes is the only way to continue to serve your customers in a way that makes them happy, thus more willing to give their loyalty (dollars!). Analyzing and reporting POS data lets you see daily fluctuations in buying trends, stock availability, and shopper behaviors and give you the ability to jump into action immediately to adapt to any changes you see.

The problem that often crops up is that gathering, arranging, and reporting your POS and EDI data is often quite cumbersome and time-consuming. Even with a dedicated person doing all of the aggregation and reporting, it might be too late to act when you finally get your data.What’s Monday’s data going to do to help you on Thursday? Luckily, there are cutting-edge technologies that do it all for you. Automatically. Up to the minute. Accelerated Analytics has been helping retail brands boost their bottom line for the past 16 years by automating the process of gathering, analyzing and reporting on the most valuable asset you have – your POS and EDI 852 data.

Optimize your inventory levels

Optimize Inventory

Photo by chuttersnap on Unsplash

The way you manage your inventory can make or break your business. Not carrying enough product can cause stock-outs and lost dollars. Your customers will shift their loyalty to another store that does seem to have the products they need. On the flip side, carrying too much inventory can eat into your ROI, not to mention take up valuable floor space. You also have to consider returns/exchanges/refunds as potential interruptions to the sales flow. Accelerated Analytics’ predictive and prescriptive software can instantly consider POS and other raw data to produce actionable insights that help you manage your inventory and grow your bottom line.

Customize the Customer Experience

Shoppers have their heads on a swivel these days; just doing a quick 180 spin will yield dizzying numbers of stores offering the same, or similar, items. So how can you make sure that these shoppers choose YOUR store or YOUR brand over the other available options?

Make them feel special.

Offer promos, coupons, loyalty points and more that are geared toward that specific customer. One size fits all doesn’t apply here; you will have to implement some workflows in order to know who wants what and how they want what they want. Find out how to fill their needs.

The way to learn  who your shoppers are and what they prefer, you will need to dive into your POS data. This information is more incredibly valuable than one would think – you can form a pretty complete picture of your customers by examining your point of sale data, or rather, reports compiled from said data. We do that.

Targeted ads are also an obvious option. For ads to work, however, you have to make sure that you are placing them appropriately. If a customer has never in their life bought a pair of 12-inch garden shears, why would they want one now? Maybe that person has been researching gardening tools & techniques, therefore, this sort of ad would be appropriate. However, if the consumer had been searching for say, high-end luxury jewelry, they likely don’t care to see an advertisement for gardening tools. Data can help with that, too.

We know that your goal is the same for each individual customer – to provide value that is relevant to them and that meets their specific needs – so we make it our life’s mission to help you get your customer’s loyalty and satisfaction. Data analytics are invaluable to a brand such as yours. You can simply open your dashboard and begin checking out the reports you’ve received from Accelerated Analytics and then decide which actions to take that will be in the best interest of the shopper and your bottom line.

Increase Sales with POS Data

Photo by Justin Lim on Unsplash

Foster lasting relationships with your customers

Consider this:

Matt Mansfield ( reported on December 26, 2018 that repeat customers spend 33 percent more than new customers and that a 10 percent increase in customer retention levels results in a 30 percent increase in the value of the company. Additionally, the average repeat customer spends 67 percent more in months 31-36 of their relationship with a business than they do in months 0-6.
Still not convinced?

Customer service.

47 percent of customers reported that they would take their business to a competitor within a day of experiencing poor customer service. This number has fluctuated to as high at 89% at times, illuminating the fact that it’s just too risky to take your customers for granted. Your business exists because of customers. No buyer, no seller.

Making sales is the goal. It’s great to make sales, and it’s important to make sales.
However, even a steady stream of one-time sales can lead to stagnation and the loss of growth opportunity. Over time, you’ll need to convert a portion of these one-time sales to loyal customers. Repeat business is proven to improve retail sales performance in the long-term, and that’s not even necessarily taking into consideration the word-of-mouth aspect of new customer acquisition.

One thing to consider implementing is a POS-tracked customer loyalty program. The premise of a loyalty program is that customers will keep coming back if you’re offering them better deals based on how much they spend with you or how often they visit your business. Such a program is not just a great way to encourage repeat business and nurture a relationship with your customer, but when taken in combination with other factors, like inventory, it also helps you to get a fuller picture of shopping trends, your customer base (demographically), and much more. Your POS system is actually a gold mine.

Customer Experience

Photo by Sara Kurfeß

Don’t brush off social media

Social media is your friend. Not only is just about everyone on it, on one platform or another, but, let’s just say it how it is – the cost begins at FREE. Such an easy-to-use and cost effective method of marketing your business, brand, service, etc. cannot just be ignored. Also key is the personal touch social media offers. You can engage with your customers and potential customers directly through posting on social media in the form of polls, videos, comments, chats, etc. Engaging your followers tends to become a snowball effect, gathering more and more interest as long as you keep moving (posting). You can post special offers for your Twitter followers, announce sales early to your Facebook fans, or talk shop with your LinkedIn connections. There’s the visual aspect, too. Enticing photographs of your merchandise can be posted to Instagram, special codes can be shared to your Snapchat adds…there’s really no limit to what you can do on social media. Simply getting your name in front of such a large audience is invaluable. And for the low price of free, it’s a win-win.

One final note: Mix it up! Take full advantage of social media. Write blogs. Run ads. Develop a loyalty program. And for the love of the shopping gods, keep your numbers in check. Utilize a reporting system to make sure you’re on track with projected inventory levels, sales numbers, staffing, etc. This will save you a lot of money and a LOT of headaches in the long run.

Learn more about how Accelerated Analytics can help you keep your numbers on track and grow your business. Or, contact us directly. We can answer your questions, schedule a demo of our reporting services, and make recommendations based upon the size and scope of your company.

Find more shopper statistics here:

Generational Differences in Your Retail Consumer Base

Digital Dealer

Buy Now

Generation Z Retail Shoppers

Photo by Robin Worrall

If it seems like Generation Y consumers are always shopping with their phones, well, they are. New research from GfK shows that 73 percent of those ages 29-38 report using a smartphone for shopping over the last six months. That’s compared with just 33 percent of baby boomers (ages 54-72) and 59 percent of Generation X (ages 39-53). Boomers are still most likely to use a home computer or laptop, GfK reports, and Generation Y is the most likely of the generations to use a tablet.

The report, part of GfK’s FutureBuy series, also notes that younger shoppers are more enthusiastic about mobile payment. More than half of those in Gen Y and Gen Z (ages 19-28, combined) find mobile payment easier, faster and more efficient than other methods; just under half say they prefer to pay with a mobile device. For boomers, those numbers are substantially lower, with only 11 percent favoring mobile payment.

One thing that is consistent across generations — and might be of note to retailers — is concern about the perceived risks of paying by mobile, felt by 57 percent of Gen Z and 61 percent of boomers. – NRF STORES

Know your consumer base

 “In the quest to build relationships with shoppers, your executions need to consider the generational profiles of your target. Programming that might be highly encouraging to a Gen Y shopper risks falling flat with a boomer. Knowing your audience has never been more important.” Joe Beier, GfK executive vice president of consumer insights

Do you know your shoppers? Can you specifically accommodate Gen Z? Baby boomers? Millennials?

Surely you have some knowledge about differences between generations. It’s easy to spot the differences through everyday life; you’ve almost certainly gained some familiarity through magazine/news articles, listicles, Internet chatter and pop culture – even a television show called Survivor: Millennials vs. Gen X. Based upon what you’ve heard/seen/read, can you identify the different generations based upon their shopping  habits?

In the year 2000

Millennial Retail Shopping

 Sara Dyer, Alabama Media Group

Right around the turn of the century, the subject of generations working together in the workforce was a source of a new kind of curiosity.  Considered a unique situation not observed at any time in the past, the multi-generational workforce was the subject of many published studies by curious researchers. The consensus reached by these researchers is that this perfect storm has occurred due to two chief simultaneous occurrences:

  1. older generations are living and working longer; and
  2. younger generations are entering the workforce sooner in life.


Purpose. A large portion of Baby Boomers won’t willingly retire until they have some other purpose to serve. When they do retire, they leave their job roles open to the next generation to fill; however, the generation following the Boomers, Gen X, is the smallest of all generations (so far). More open jobs + not enough Gen X-ers to fill them equals opportunity for Gen Y-ers to vie for the promotions that will put them into those roles. Hence, younger generations are influencing the culture of the workplace sooner than preceding generations.

Then and Now

Generation Z in Retail

Saved by the Bell, 1989 – 1993

The documentation produced by the studies of 2000-2001 proved to be useful in helping different generations learn to understand each other at that time. This documentation, while interesting and helpful, did not seem to account for demographics or personal/familial history, which are HUGE factors in shaping how an individual prioritizes his or her next move. However, the studies proved to be a good jumping off point, and evolving studies will help to form a more complete story. Think about how vastly different the 90s were from the 2000s. Many things affected society that nobody ever even considered before, such as 9/11, technology and how we use it to stay constantly plugged in, a popped housing bubble followed by a deep recession, the first black US president, and so on. These events have changed the way we see life as a whole, our values, and how we each individually live our day-to-day lives. It makes you wonder what is to come in the next decade that we haven’t even thought of yet, how it will continue to change society, and how people in different generations will keep up with the constant evolution.

Going Forward

The world certainly seems smaller these days. However, perception still differs from person to person, depending heavily on upbringing, demographics, beliefs, age etc. Differences in outlook are not meant to drive a wedge between different groups of people, but instead to drive empathy, interaction and understanding. The retail landscape depends on different outlooks coming together to fill everyone’s shopping needs. While generational stereotypes exist, it’s important to avoid automatically categorizing consumers based upon their age, just as we know to avoid stereotyping consumers by skin color, gender, disability, etc.

That said, the evolution of society continues to snowball, resulting in varying opinions regarding beginning and ending dates establishing generational boundaries. According to Kent State, researchers now describe the post-1980 generations in three groups, based on a number of certain factors.

The dates below are averaged ranges from a handful of studies.

  • Gen Y – born 1980 – 1985
  • Millennials – born 1986 – 1995
  • Gen Z – born after 1995
Gen Z Retail

Photo by Julián Gentilezza

The biggest societal jump happened between Millennials and Gen Z with the rapid evolution of technology. Admittedly, we as a society have a marked tendency to define the generations by their use of technology. The defining categorizations are as follows:

Gen Y are tech literate. Close to late teens/early adulthood during the advent of rapid technological advancements, Gen Y has adapted to the technological landscape, but can fondly remember a childhood before the tether of the Internet and mobile devices.

Millennials are techsavvy. The most staggering leaps in technological advancement happened during the formative years of Millennials’ childhood.

Gen Z are digital natives. Unlike the Millennials before them, Gen Z kids were born into the majority of advanced tech of today, and played with tablets and smartphones rather than ride bikes and climb trees.

Gen Y and Millennials learned technology as it became available to them. As such, best practices for use were not yet established, causing unforeseen havoc as technology continued to advance to the point that private information posted on social media began to creep into the professional lives of unsuspecting young professionals when employers began ‘social-stalking’ employees and prospective employees to help determine employment viability. Digitally-native Gen Z-ers, however, grew up with the lessons (learned the hard way by their Gen Y and Millennial parents) and thus are inherently smarter with privacy, info sharing, discernment of clickbait, catfishing and fake news sites, than their predecessors.

Of course, we are still learning on our feet. Gen Z is working its way into the workforce and therefore into the retail landscape. As we continue to learn by trial and error, we’re taking notes and learning to adjust and adapt quickly enough to satisfy the needs of all consumers – that’s the goal, anyway. From differences in preferred means of communication (where do you market your products or services to each generation? Email? Traditional mail? Snapchat?) to rapidly changing everything, the perceptions and experiences of each generation are important ingredients to forming and figuring out what’s next – not just in retail, but in all parts of this thing we call life.

Sources:, NRF’s online magazine;

Retail and Artificial Intelligence: What’s Next?

Retailers are constantly talking about the future, but what technologies are going to take them there?
Retail Artificial Intelligence

When we think about innovations like chatbots, personalized product recommendations, dynamic pricing and programmatic display, there’s one common denominator. All of these are great examples of how artificial intelligence can be a game-changer for a multichannel retailer.

Over the next three to five years, AI will play a significant role in the multichannel retail market. It will help differentiate the winning organizations, as well as determine which ones close their physical and digital doors.

It’s easy to think of AI as a buzzword, but based on a study of more than 13,000 consumers, brands with the most sophisticated, personalized customer experiences have higher satisfaction and Net Promoter Scores, as well as higher retention. Using AI, machine learning and technology to highlight what makes the brand and their buyers unique is what sets apart retailers like Sephora and Nordstrom.

Global retail sector technology spending is expected to grow 3.6% year-over-year to reach almost $203.6 billion this year. Similar spending is projected for the next two years as well, with the fastest-growing category being software. As consumer expectations for highly-connected experiences continue to increase, it’s critical for retailers to become versed in how to buy and apply AI — and quickly.

This post is based on an article written by Jason Grunberg for SailThru.

International Builders’ Show 2019

Featuring more than 1,500 exhibitors, the 75th annual International Builders’ Show, held February 19-21, 2019 in Las Vegas, proved to be the biggest in a decade, proving to us that the home building industry continues to flourish.

2019 International Builders Show The show was part of Design & Construction Week®, which saw more than 100,000 attendees. The IBS exhibit floor covered more than 600,000 square feet, where attendees browsed the latest home technology products, watched live interactive building demonstrations, participated in over 125 education programs presented by thought leaders in the industry, enjoyed happy hours, music (the closing concert welcomed the Goo Goo Dolls!), comedy (opening ceremony featured Dana Carvey as well as Blue Man Group) and networking with the best in the industry while collecting IBS swag along the way.

International Builders Show With roots tracing back to the 1940s, the International Builders’ Show now celebrates 75 years of home building, products and innovation with over a million square feet of space offering numerous events and new features including the Wood Flooring Pavilion and the Jobsite Safety Zone, which provided safety demonstrations, microlearning sessions and networking opportunities.

Classic IBS favorites made a return, including:

  • High Performance Building Zone: Live interactive demonstrations to improve efficiency in all areas of the house.
  • The Centrals: Comfortable lounges dedicated to specific market niches including remodeling, custom building, multifamily, 55+ housing, international, design, and sales.
  • Pavilions and Special Interest Areas: The newest trends in home and business technologies
  • Outdoor Exhibits: Entire homes are constructed especially for the show. The light dusting of snow couldn’t keep us inside!

Other events included industry awards, all-stars celebration, green home tour, awards gala and more.

Click here to read the full recap of IBS75

2019 International Builders Show International Builders Show #IBS2019 #IBS75years


Using your POS Data to Maintain Optimal Inventory Levels


POS Data for Inventory Management

POS Data:

More than Numbers

Companies can draw insights about consumer behavior using POS data, which defines an intricate correlation between purchases, inventory, seasons and other contributing factors. These sets of data hold a lot of value, but in raw form, the information can be difficult to work with; after being cleaned up and formatted by a team of analysts, the data can be considered usable.

Inventory Can Make or Break Your Brand

The O-Bomb: Out of Stocks

Out-of-Stock (OOS) is a dangerous phrase among retailers, since it slows sales when real demand strikes. POS data reveals a trend that tells which of the products are in demand at what time during a day, week or year. This helps retailers prioritize stocking the right products in their stores. The biggest advantage you can enjoy as a retailer is to also manage different product categories with enough stock, seamlessly. Hourly sales data with significant gaps during peak sales periods would determine how to tackle with OOS issues to every detail.

Sales Trends

POS data provides the sales and profits earned from each store. optimizing the productivity of a store can help boost the profitability of each store. The comparable data of how revenues are occurring is easily accessible from POS data. It enables productivity at a granular level, which helps to get to the details of each product, category, shelf and store.

Promotional Events

By utilizing POS data to its fullest, retailers can make more accurate decisions in a shorter amount of time. The promotion is optimized to perform well; thanks to POS data reports, management knows exactly what is happening at the points of sale, how consumers are responding to specific promotions, the effects of outside factors like weather, holidays, local events, etc. As more data is gathered and utilized, it is possible to produce calculations of ROI – calculations that can help to plan & execute future promotions. Promotional pricing can be optimized using this data, as well.

Overcoming Challenges in Inventory Management

How Accelerated Analytics Can Help:

Sending your goods to distributors and retailers doesn’t necessarily mean that it will make it into a customer’s cart; events such as returns, exchanges and refunds interrupt the flow of sales cycle. POS data helps predict trends around such interruptions, creating a more unified flow of distribution and sales.
The POS data further helps to gain deeper insights into consumers by analyzing which specific products they are buying and what products are bought together. This information helps retailers plan for future promotions, as well as planning store layout by putting together products likely to be bought together.

POS data is a gold mine for retailers to understand consumer behaviors and the impact of sales at each store, but even though most retailers collect and store POS data, they don’t know how to make it work for them. Harnessing such large data sets require powerful, deep analysis, so it’s best done using advanced analysis tools. Our predictive and prescriptive software can transform and assimilate POS data and other raw data into actionable insights – insights that will ultimately result in more sales, thus a better bottom line. POS Data Reports

How Gen Z is Changing the World of Retail

The latest generation of consumers
is prompting retailers to re-frame their thinking about the customer experience today compared to what it was just
a decade ago.
Technology is changing the way we shop, thanks to the knowledge, habits and expectations of the generation we
know as Millennials – they’ve driven big changes to business worldwide.

But Millennials are no longer the youngest generation of consumers. The next generation, known as Generation Z,
is coming up quickly on the heels of Millennials, and these consumers have already begun to bring even bigger
changes – and challenges – to retailers. Millennials made an enormous splash when they became independent
consumers, and Gen Z-ers – the first ‘digital natives’ – are disrupting the world of retail now.

Gen Z-ers (born between the mid-90s to mid-2000s) are 26%32% of today’s population, the largest single
segment, and they don’t remember life before mobile phones, social media or the Internet. This tech-savvy culture
means that these shoppers have no patience for any retail/marketing trickery, and it’s very important for retailers
to remember this; unlike previous generations of kids whose retail preferences were not heard or heeded, 93%
of parents of Gen Z-ers say they actively influence family purchasing decisions. They also make said decisions with
heavy influence of social media platforms; with their mobile devices at the ready, this global population of
2 – 2.5 billion (and 70 million in the U.S.) hold up to $143 billion in buying power.
Because of the significant influence Gen Z has as shoppers—even the youngest among them–retailers are beginning
to realize the generation’s disruptive impact before other business sectors.

What Retailers Should Know About Generation Z

Gen Z and Retailers

The majority (77%) of Gen Z-ers prefer to shop
in brick-and-mortar stores.
Creating the right in-store experience is crucial. From offering personalized customer service
to ensuring items are in stock, retailers can make a positive impression on this desired demographic—because they may not
get a second chance. That said, astute retailers unify their physical stores with the online world. Deeper data mining
allows brands to use factors such as social influence and digital behavior to cater to the consumer.

Gen Z shoppers expect a seamless digital-to-physical experience. This generation relies heavily on mobile devices and
expects fast-loading websites and an omnichannel experience. If they research an item online, then go to the store to see
the item, they want that integration to be seamless and cohesive.

Gen Z-ers consider value over cost. Unlike the millennials before them, Gen Z-ers are careful with their funds. They’ll support
brands they believe in, but not to the detriment of their future. Watching their parents struggle through the recession has
made this generation wary of credit and debt, less prone to taking it on. Previous generations had a “buy now, pay later”
attitude – a concept that arguably caused the recession, so Gen Z is, thankfully, showing Gen Z Shoppers signs that they’ve learned from
the mistakes of their parents.

“Data is at the forefront of everything, and the customer is the center of everything.”
Janet Sherlock, Ralph Lauren CIO

Final notes

Information collected through foot traffic-monitoring
technology can be instrumental in giving retailers better insights to optimize store layouts to enable the consumer to find
what they are looking for. In addition to providing more detailed customer profiles, collected data allows retailers to more
deeply understand how consumers shop in the store, including what products and displays catch their eye and what they eschew.
Important: Although retailers use customer data for the benefits it can help provide to said customer, the retailer must be
transparent about the collection, disclosing the benefits it will provide customers (convenience, time savings, customized
recommendations, etc.) as well as what the retailer gets out of it.
These days, the collective expectation is that the shopping experience will be similar to social media interactions – tailored
and instantly attainable. To make the most of the eight-second attention span of the average Gen Z-er, retailers must embrace
and leverage the technology that is increasingly available and always evolving.



Client Spotlight: Vera Bradley

Vera Bradley Capitalizes on Opportunities by Leveraging POS Data Vera Bradley POS Data Reports

In 2013, when the business leaders at Vera Bradley were bringing on Dillard’s, their first big department store, they knew it would be critically important to be able to see their sell-through. When they asked the team at Dillard’s for sell-through data, Dillard’s quickly introduced Vera Bradley to Accelerated Analytics and a strong and valuable relationship began. As Vera Bradley expanded into additional department stores, Accelerated Analytics was with them every step of the way.


As Vera Bradley expanded into new retailers, they knew that one of the keys to their successful growth would be the ability to compare sales across retailers. Relying solely on each individual retailer for sales data would mean looking at multiple reports with inconsistent formats and verbiage. Deriving the comparisons and analysis that would be essential to the success of their growth strategy would be time consuming and challenging. Accelerated Analytics provided a solution that allowed Vera Bradley to see all of their sales data across retailers, in a consistent format.

“We can react quickly because we have visibility; patterns are emotional and numbers don’t lie.”
– Heidi McClain, Business Planner, Vera Bradley

Vera Bradley Utilizes POS Reporting Data Visibility Empowers Vera Bradley to Make Timely, Informed Decisions

From the business planners to the account managers and sales team, multiple departments use our POS reports and analysis provided to Vera Bradley by Accelerated Analytics. Business Planner Heidi McClain values the ability to see the “store and SKU attributes how we want to see them as opposed to how the retailer provides them.” She explains that the SKU-level sales versus top-level sales “speak volumes to our account managers.” McClain provides a weekly selling summary to the sales team, enabling them to compare sales across retailers, identify strengths and opportunities, and react quickly. Vera Bradley’s Director of Information Architecture says that Accelerated Analytics is “like having an extension of my team,” and points to the value of the sell-through data as one of the most valuable aspects of the Accelerated Analytics tool. Accelerated Analytics data and reports empower the Vera Bradley team with the knowledge of what’s selling and what’s not, and enables them to react quickly.

• In 2015 when Vera Bradley launched new doors with one of their existing department stores, from day one they were able to identify opportunities in current inventory and quickly partner with them to make adjustments.

• When the Vera Bradley team needs to know how an account is performing they can view its success geographically and easily see its percent to total.

• When one of their department store partners passed on a top pattern, Accelerated Analytics data helped show Vera Bradley how well the pattern was performing within other retail partners. That gave the store the confidence to add it to their assortment. Since adding it, this retailer’s sales have continued to increase and the pattern is one of their top performers to date.

About Vera Bradley Guided by their founders, Patricia R. Miller and Barbara Bradley Baekgaard, Vera Bradley has earned a reputation as a leader in the gift industry. Creating stylish quilted cotton luggage, handbags and accessories, the company combines smart product designs with distinctive and colorful fabrics and trims.