All posts by Marilyn Bernardo

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Planalytics will be a Big Ideas exhibitor at the NRF 2023 Retail’s Big Show in New York City, additional details below.
Visit us at booth 3933! 

Nailing demand forecasts: From machine learning to replenishment and everything in between

Tuesday, January 17th, 2023
9:15 to 9:45 am | Expo, Level 3, Expo Stage 5

Speakers include:

  • Ross Giambalvo, Vice President of Inventory Management, H-E-B
  • Jeremy Elster, Data Science Manager, Chipotle Mexican Grill
  • Tyler Scott, Senior Director, Demand Planning/Retail Support, Albertson’s

Learn how H-E-B, Albertsons, and Chipotle are capturing additional sales and margin by staying ahead of an always present and highly impactful driver of demand volatility – the weather. The weather’s influence on consumer purchasing is a key reason for sales swings but it is not an unknown. Hear how these leading retailers are using weather-driven demand analytics to precisely quantify and integrate these metrics into machine learning environments, performance reporting, demand forecasting solutions, store-level replenishment, digital marketing, and more. Attending NRF? Register here.


Visit us at booth 3933! If you would like more information about Planalytics, or to schedule a time to meet at the event, contact dfrieberg@planalytics.com.


For additional NRF event information, Click Here.

 

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Cognira + Planalytics: The Impact Weather-Driven Demand Has on Promotion Performance

Why Integrating Weather-Driven Demand Analytics
with Promotion Management Can Improve Retailer’s Bottom Line

Often one of the first things people do is check the weather when starting their day. Weather plays a huge role in the clothes we choose to wear, the activities we do for the day, the food and drinks we consume, and even our emotional state.

Recent research has shown that weather has the second biggest impact on consumer behavior right after the state of the economy. Different weather states can determine how consumers shop, what they purchase, when merchants launch new lines, and when sales seasons begin.

With the power of advanced technology, retailers now have the ability to pair weather data with their strategies in an effort to meet their customers’ needs.

Throughout the article discover the impacts weather-driven demand has on promotion performance.

Weather-Driven

How Weather Impacts Promotion Performance

One of the major keys to a successful promotion is if it’s customer-centric. Today, top retailers follow these strategies to ensure their promotions align with their customer’s behaviors:

How Weather Impacts Promotion Performance 1. Integrate Customer-Centric strategies across ALL Channels
2. Leverage advanced technology
3. Optimize Forecasting for better customer behavior insights
4. Digitize and centralize the entire customer experience

One area that is often overlooked? Understanding the weather’s impact on your customer’s priorities.

By combining both promotion management strategies and weather-driven demand analytics, retailers can further optimize their promotions by providing the right products, at the right price, in the easiest obtainable way for their customers.

Here are a few examples of how weather impacts promotion performance:

Better Forecasting, Better Predictions

Better Forecasting, Better Predictions By including weather analytics in the forecasting stage, retailers are able to make even better predictions about purchasing patterns. Why? Because it can give accurate insight into a specific product or location that will be directly impacted by weather.

With more information comes more accuracy, meaning retailers can feel confident about what the demand will look like for the specific product, how much they will need to order, and ensure the promotion will be released to the right audience, at the right time, and to the right location.

Enhanced Decision-Making

Enhanced Decision-Making Business weather intelligence can give retailers insight up to 2 weeks in advance of their promotion running. This allows merchants to adjust their promotion strategies if there was a shift in demand due to weather.

 

Improved Inventory

Improved Inventory

If there is a drastic change in weather from when previous promotions were run, retailers risk ordering too much (which can lead to waste), or not ordering enough (resulting in lost sales).

By layering specific predictive demand analytics onto current promotion solutions, retailers are able to see how changes in upcoming weather conditions will either increase or decrease demand and update their orders accordingly to avoid too much or too little inventory.

Use Case Scenarios

Now that we understand the impact weather has on promotion performance, let’s provide a few use-case examples of how weather analytics can work alongside a promotion management solution.

Improved Inventory

Tina works in buying and forecasts promotions for inline and online items. She is going to run a key wintertime promotion on a product and wants to forecast how many units she should purchase.

By utilizing business weather intelligence within her promotion solution, Tina is able to gain insight into the:

1. Promotional lift
2. Weather lift

Through her analysis, she was able to see that where the weather had been favorable, the sales were higher than the promotional and weather lift suggested. This synergistic effect shows Tina that the product is highly sensitive (in a positive way) to weather and will perform even better when paired with a promotion.

By having access to this information, Tina is able to:

– Create a successful promotion
– Generate orders ahead of the demand spike
– Avoid out-of-stock situations

Enhance Decision Making

Phil, a category merchant for a grocer, has created a promotion on hotdogs to run throughout the heat wave in New Hampshire and submitted it for approval. Two weeks before the promotion is set to run, he receives an alert about drastic changes in the weather. The weather went from warm and sunny, to gloomy and heavy rain.

Since hotdogs are grilled outside, there has been a drop in demand than what was originally anticipated. Phil can either kill the promotion, reduce the amount of product, or run a different promotion on another product that will perform better.

Avoid Waste

An abnormal snowstorm is predicted to happen in Minneapolis, Minnesota when a grocery merchant plans on running a promotion for a fresh product. Though the merchant is running the same promotion across all of the stores in the US, the promotion in Minneapolis is no longer predicted to run as well.

With the help of weather analytics, merchants are able to see two weeks in advance the drastic drop in demand for that specific region. Because the product on promotion is fresh, they risk dealing with waste.

To avoid having too much product on hand, the merchant changes the amount that needs to be ordered ahead of time.

About Cognira

Cognira is the leading Promotion Management solution provider for retailers and wholesalers, making it easy to collaborate across departments, analyze past performance and run smarter, more effective promotions that meet their customer’s needs.

Cognira’s single solution leverages data science and AI to effectively manage the entire end-to-end promotion lifecycle.

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Weather & Retail Myth #4: My Products Aren’t Seasonal, So the Weather Doesn’t Affect Me

Many categories — from lawn fertilizer to knitwear to sun care — are obviously impacted by the weather, but it can be surprising to learn how much non-seasonal products are also affected. Over 90 percent of a business’s annual weather-driven sales come from day-to-day changes in temperature and precipitation that influence consumer shopping patterns and behaviors.

When analytics are used to isolate how much of a product’s sales volatility is weather-related, some revealing insights emerge. Jewelry is three times more weather-sensitive in January than during the rest of the year. Why might this be? In January, consumers are often looking to redeem gift cards and take advantage of post-holiday sales. Favorable weather in January (typically warmer and drier than normal) can drive store traffic and lift jewelry sales in advance of Valentine’s Day. Of course, when the inverse occurs and the weather is cold and snowy, jewelry sales can be limited.

Similarly, coffee — a daily habit for many — sees sales swings of 5 percent on average due to the weather. These swings vary based on the time of year and market; major markets in the Northeast can experience strong coffee demand of 10 percent above normal levels when cool weather extends into spring months.

Weather related traffic drives sales of non-seasonal items

When it comes to store or site traffic, “a rising tide lifts all boats.” If favorable weather conditions bring customers into stores for a seasonal item such as charcoal, there is a good chance they may pick up additional items on their shopping trip (ketchup, shampoo, etc.). On the other hand, if poor weather keeps customers away, a mass merchant is going to see sales fall across the board, including in non-seasonal departments like home goods, toys, and electronics.

Finally, deweatherizing sales histories to correct weather-based sales distortions drives forecast accuracy improvements. It is common for businesses to realize a 50-200 basis point accuracy improvement on nonseasonal, high volume, year-round categories. This results in measurable financial benefits by increasing in-stock levels and reducing inventory carrying costs.

Check out the 5 Myths About the Weather & Its Impact on Retail from the NRF to learn more.

MORE NRF & PLANALYTICS NEWS:

Planalytics is excited to be exhibiting and participating in NRF 2023 (Retail’s Big Show) in New York City in January. Visit the NRF’s website to learn more and to register!

Visit Planalytics at Booth #3933 and be sure to attend a panel session with H-E-B, Albertsons & Chipotle: “Nailing demand forecasts: From machine learning to replenishment and everything in between” on Tuesday, January 17th. Hear how these leading retailers are using predictive weather-driven demand analytics to better understand consumer purchasing and capture additional sales and margins.

 

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Stores See Moderate Gains, Questionable Margins

By David Moin

Retailers overcame inflation concerns and a deep early December lull to post midsingle-digit sales increases for the holiday season to date and hope for further gains via clearances in the weeks aheaday 2022.

It wasn’t a blockbuster or a bust. Retailers emerged from the holiday season with midsingle-digit revenue gains, questionable margins and leftover fall and holiday inventories. They now look forward to at least three weeks of intense clearance activity to shed the excess, generate early spring selling and make up for business lost during last week’s lethal “cyclone bomb” from Mother Nature.   . . .

Overall, the weather lifted demand for need-based categories as well as coldweather gift-giving categories throughout December leading up to Christmas,” said Evan Gold, executive vice president of Planalytics, a consulting firm that helps retailers plan inventories based on weather forecasts. “The last two weeks of December leading up to Christmas were much colder than last year, helping to drive demand for seasonal categories.

“But looking ahead. January will be warmer than last part, and there will be limited opportunities for clearance of cold-weather categories on a year-over-year basis.” . . .

To read the full article, Click Here.


For more information about Planalytics, Contact Us.

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Weather & Retail Myth #2: It All Evens Out in the End!

“Sometimes the weather hurts me, sometimes the weather helps me.” While this adage often rings true, it does not mean that positive and negative weather simply even out over the course of a selling season, fiscal quarter or even a year. The timing, location, strength and duration of favorable or unfavorable weather makes a big difference.

Consider the following examples:

– PROFITABILITY: A negative 25-percent weather-driven demand impact on winter coats in November is not offset by a 25-percent weather-based demand boost in January. Further, there is a lot more profit in a November sale compared with the end of the season when merchandise is marked down heavily for clearance.

– LOST SALES: When a winter storm keeps people at home, some sales are never made up. Yes, the weekly grocery run is often made a day or two later, but if someone doesn’t stop for a cup of coffee on the way to work because a snowstorm keeps them at home, they don’t buy two coffees the next morning to “make up for it.” The same is true for other categories or for impulse buys.

– TIMING: Warmer-than-normal temperatures in the early spring can be great for do-it-yourself retailers as consumers head to stores for live plants and other lawn and garden items. However, if these retailers have a less favorable start to the season, improved weather in May or June will not have the same effect. For many consumers, the optimal “window of time” has passed for certain outdoor projects (or other seasonal items like apparel or décor). DIY projects will be downsized or skipped altogether as the calendar shifts the consumer’s attention to other priorities and activities.

Unlike Newton’s third law of motion, there is not really “an equal and opposite reaction” when it comes to weather and its business ramifications.

Check out the 5 Myths About the Weather & Its Impact on Retail from the NRF to learn more.

 

More NRF & Planalytics News 

Planalytics is excited to be exhibiting and participating in NRF 2023 (Retail’s Big Show) in New York City in January.  Visit the NRF’s website to learn more and to register!

Visit Planalytics at Booth #3393 and be sure to attend a panel session with H-E-B, Albertsons & Chipotle: “Nailing demand forecasts: From machine learning to replenishment and everything in between” on Tuesday, January 17th. Hear how these leading retailers are using predictive weather-driven demand analytics to better understand consumer purchasing and capture additional sales and margin.

 

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Weather & Retail Myth #1: You Can’t Plan for the Weather

What does 53°F and light rain mean for sales? The answer is different in Chicago than in Charlotte; it varies if it is a day in March or October. The weather’s influence on consumers is complex and nuanced and temperature or precipitation data is easily misinterpreted and misused. As a result, many businesses believe planning for weather’s impact on sales is an exercise in futility.

However, ignoring the effect of something with such a profound impact on consumers’ day-to-day lives can lead to severe miscalculations in everything from sales and inventory to markdowns and staffing levels. To help retailers understand how to anticipate and plan around the weather, the National Retail Federation and Planalytics have identified five common weather myths that affect retailers and how to effectively incorporate weather considerations to make better decisions.

MYTH 1: YOU CAN’T PLAN FOR THE WEATHER

Because specific weather events — heat waves, snowstorms, cold snaps, etc. — cannot be precisely forecasted in advance, it can be challenging for businesses to react to near-term opportunities or risks. This is particularly true for retail, where decisions around demand planning, supply chain operations, labor scheduling, marketing and more are determined weeks, if not months, in advance. However, viewing the weather as “a force that can’t be reckoned with” can lead to significant miscalculations in sales or inventory forecasting. Instead, retailers should proactively account for weather’s impact in three areas of business:

PLANNING: The weather — and its impact on business — only repeats from one year to the next about 15 percent of the time, though it’s common for plans to be heavily based on or influenced by the prior year. This leads many companies to unwittingly embed the previous year’s weather variations and sales impacts into their business forecasts. Retailers can remove much of this built-in error by deweatherizing their sales history. This process uses weather-driven demand calculations to systematically remove weather-based sales distortions and provide a cleansed, normalized baseline for planning. Weather-driven demand is the quantification of the impact of weather — and weather alone — on demand for a product or service.

Through deweatherization, retailers improve total enterprise forecast accuracy by several percentage points on average, and up to 50 percent for specific product categories.

LOCALIZED STRATEGIES: There is a danger of creating false answers through an oversimplified approach. Without analyzing weather and sales information at both the market and the weekly level, it is easy to get the weather drivers and volume impacts wrong. For example, an assumption that every one-degree temperature increase delivers a 7,500-unit sales increase will be inaccurate when looking at different locations, distinct times of the year and various merchandise categories.

STAFFING: Retailers are not only managing the cost of carrying inventory; they are also charged with staffing stores appropriately to manage the influx of shoppers. Weather has a direct influence on store traffic. By utilizing weather-driven demand calculations, businesses can prepare for and quickly adjust store staffing to better accommodate varying traffic levels, maximizing the efficiency of individual stores and better managing to budgets.

Check out the 5 Myths About the Weather & Its Impact on Retail from the NRF to learn more.

 

More NRF & Planalytics News 

Planalytics is excited to be exhibiting and participating in NRF 2023 (Retail’s Big Show) in New York City in January.  Visit the NRF’s website to learn more and to register!

Visit Planalytics at Booth #3393 and be sure to attend a panel session with H-E-B, Albertsons & Chipotle: “Nailing demand forecasts: From machine learning to replenishment and everything in between” on Tuesday, January 17th. Hear how these leading retailers are using predictive weather-driven demand analytics to better understand consumer purchasing and capture additional sales and margin.

 

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Holiday Season Insights from the National Retail Federation & Planalytics

On December 8th, Planalytics hosted a Holiday Update webinar with special guest Katherine Cullen of the National Retail Federation (NRF). A recording of this presentation is available here.

Katherine is the NRF’s Senior Director, Retail & Consumer Insights and she began the presentation with a look at their holiday sales forecast (+6-8%) and discussion of how spending would vary amongst across different income levels.

“Of course, we don’t want to discount the impact of inflation,” said Katherine. “It is important to keep in mind that lower- and middle-income households are certainly feeling the most pressure and have the least amount of flexibility to adjust spending.” On the other hand, higher income households are planning to spend more, as the image below shows.

 

 

Katherine went on to discuss trends the NRF is seeing regarding chosen shopping destinations (clothing stores, electronics stores, discount stores, etc.) as well as research on when the holiday shopping season starts for consumers and the reasons some shoppers start buying before November.

The NRF noted there was a lot of momentum heading into the Thanksgiving and retail sales during the Black Friday weekend exceeded expectations. Katherine reported that “we saw a record 196.7 million consumers shop both online and in stores starting Thanksgiving Day and continuing all the way through Cyber Monday.”

 

 

Planalytics’ Executive VP, Evan Gold, joined the discussion to highlight how the ever-important external variable retailers must account for – the weather. “You can’t overstate the importance that the weather has during the holidays,” according to Evan, who also noted that retailers shouldn’t buy into the myth that people will be shopping regardless and therefore the weather doesn’t matter. “It influences the channels the customer shops from,” Gold said and the weather “will directly influence the items customers are putting in their shopping carts, both physically and virtually.”

Evan shared how the weather has and will impact consumer demand trends this holiday season starting with October when colder temperatures in the East provided a positive start for sales of seasonal items. In November, the more favorable conditions pivoted from the East to the West, where clothing, hot foods, and other winter season products saw a boost in sales.

For December, Planalytics is projecting positive weather-influenced sales for many retailers compared to last year (see image below).

 

Listen to the webinar recording to get all the details.

 

 

More NRF & Planalytics News!

Planalytics is excited to be exhibiting and participating in NRF 2023 (Retail’s Big Show) in New York City in January. Visit the NRF’s website to learn more and to register!

Visit Planalytics at Booth #3393 and be sure to attend a panel session with H-E-B, Albertsons & Chipotle: “Nailing demand forecasts: From machine learning to replenishment and everything in between” on Tuesday, January 17th. Hear how these leading retailers are using predictive weather-driven demand analytics to better understand consumer purchasing and capture additional sales and margin.

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Improving Demand Planning Accuracy by Integrating Weather Analytics

Our partners at Enhanced Retail Solutions have published a step-by-step overview for integrating weather-driven demand analytics into retail plans and demand forecasts.

“Estimating future sales is increasingly difficult with so many factors to be taken into consideration. The economy, inconsistencies in stock levels, changes in assortments and consumer shopping patterns to name just a few. Most inventory planners rely on historic sales to create their forecasts. However, that history may need to be adjusted to reflect a more realistic basis. While many forecasts are adjusted for seasonality, more robust adjustments can be made by integrating weather related demand. For product categories that are affected by weather- including temperature or precipitation- fine tuning a forecast based on this feature engineered demand signal significantly improves the predictability of future sales. ERS and Planalytics have partnered together to help companies improve their forecasting accuracy.

Visit the ERS website to read about the following step-by-step process that enables businesses to optimize forecasts by accounting for the weather’s sales impacts, driving improved planning accuracy and increases in sales and profitability.

Step 1: Data Requirements and Technology Platform

Step 2: Collecting the Data

Step 3: Understanding the Basic Logic

Step 4: Adjusting for Lost Sales

Step 5: Fine Tuning with Weather-Driven Demand Analytics

Step 6: Putting the Information Together

“Improving forecast accuracy can have a significant impact on both sales and profit. And because your inventory utilization is better, the cost of capital goes down. If you are currently forecasting in a spreadsheet, you could save a significant amount of time by automating. One of the benefits of the BI tools is seeing exceptions- items with low or high inventory, changes in trends or buys that are needed right away, and accounting for demand fluctuations due to the weather. It serves as an alert system which helps you quickly react to opportunities and address risks.”

 

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