Planalytics is sponsoring and exhibiting at NRF 2022 on January 16-18, 2022 in New York City, NY.
Planalytics will be exhibiting at Booth #5346.
If you are interested in learning more or arranging a time for a meeting during the conference, please contact email@example.com.
By: ExchangeWire PressBox
Peer39, the leading global provider of advanced contextual intelligence, today launched the Contextual Data Marketplace, a first-of-its-kind data Marketplace that gives advertisers direct access to innovative cookie-free data sets from emerging contextual data providers, while making these providers’ insights more easily accessible to programmatic ad buyers.
The Contextual Data Marketplace extends Peer39’s sophisticated layered system of components, processes, models and technology to data partners, helping these providers create new data products and then make them available, at scale, on leading DSPs. At launch, buyers will have access to new contextual insights from branded suppliers such as Newsguard, HotSpex Media and Planalytics, among others. More than a dozen more suppliers will come on board in 2021. . . .
. . . As the ad industry moves toward a post-cookie future, brands and agencies need ways to deliver targeted advertisements in privacy compliant fashion. Demand is steadily growing for data sets that provide insight and the understanding of context, making ads relevant for users with new and expanded levels of accuracy. Some of the companies entering the marketplace have long provided valuable insights to brands outside of the advertising segment. Many have experienced strong demand for their solutions in the marketing industry but have been challenged by the upfront costs and lengthy investment required on the technology and relationship front.
“The move away from behavioural signals has helped advertisers see that there’s so much more contextual insight available beyond page context,” said Frederic Fox, CEO of Planalytics. “The Product Demand Index is a powerful new contextual targeting option for brands, enabling them to choose audiences using location-specific analytics derived from weather insights. The easy access to the programmatic space will only help advertisers find greater scale for product categories that are in demand by consumers.”
Through the contextual marketplace, Peer39 serves as the conduit for advertisers to access and utilise these diverse contextual data sets, and for these data sets to become more widely available, via Peer39’s existing marketplace infrastructure. . .
How it works
. . . Through the Contextual Data Marketplace, Peer39 will extend its capabilities, algorithms, models, and technology, offering third parties unique capabilities, so that they can use them in model development or enhancement of their own offerings. Through this collaboration and use of marketplace toolsets, data partners will be able to produce data and publish back into Peer39’s contextual infrastructure, routing the data in real time globally. These new data categories are instantly available across a vast global programmatic ecosystem through leading demand-side platforms.
Planalytics is a Blue Yonder partner and will be attending and sponsoring this year’s Blue Yonder ICON conference from April 21 – 23, 2021.
Sponsored content by Planalytics
• The weather influences consumer buying behavior everyday – and it never stops changing; no other external variable shifts demand trends as immediately, frequently, and meaningfully.
• Retailers improve forecast accuracy when data-driven weather analytics are incorporated into planning, allocation, and replenishment processes and better align store-level inventories with consumer demand.
• Misaligned inventories lead to higher costs and reduced profits; inventory costs, markdowns, and shrink will be higher for retailers that ignore the impacts of weather-driven sales volatility.
Retailers have long looked at localization as a powerful way to improved conversions, total receipts, and customer satisfaction or loyalty. Localizing assortments and having the right amount of inventory available in stores when customers want to buy is a must if businesses want to realize localization’s promise and financial benefits.
Unfortunately, localization remains elusive for most retailers for a variety of reasons. Often, it is a lack of capabilities in a retailer’s existing software solutions. Or, finding a workable way to incorporate the “voice of the store” into processes has proven to be very difficult. And possibly the biggest hurdle to success has been the lack of access to critical market-level analytics.
On this final point, retailers may not realize that one very important piece of market-level intelligence is now accessible and applying it to the business has never been easier. The emergence of weather analytics that are precise, scalable, and presented in a business context (product volumes, not temperatures) is allowing retailers to optimize local inventories and improve both sales and margins.
What’s more “local” than the weather? When it comes to external variables, nothing is more consistently and directly impactful on sales than the weather. Integrating weather-driven demand metrics into core merchandising processes is not a long, drawn-out project and, once implemented, retailers can start capturing benefits in a matter of weeks.
By applying weather analytics across the business, retailers can add up to a 2% to total topline sales. Better availability leads to more sales and profit. But weather analytics also help on the expense side of the ledger. Inventory costs, markdowns and shrink are three primary examples.
Inventory costs: First off, retailers gain a one-time boost to their balance sheets by incorporating weather analytics. The benefit can be measured by looking at working capital improvement as a percent of cash and cash equivalents. For grocery, a 3-5% increase in working capital relative to cash is a common range. For DIY/home improvement and general merchandise chains, gains of 20% or more can often be achieved. Through a process called “deweatherization” retailers correct for the weather noise in historical sales and generate first-year savings as a result of initial inventory realignment or clean-up. This initial inventory reduction produces working capital by reducing the total inventory in the retailer’s system via improved forecast accuracy and optimized safety stocks.
Going forward, the improved planning accuracy produces annual costs savings by reducing excess stocks and inventory carrying costs. These savings enhance margins, with many retailers seeing 20 to 70 basis points in incremental profit as a result.
Markdowns: Clothing chains, sporting goods retailers, department stores, home centers, and other retailers can also utilize weather analytics can help limit margin-eroding markdowns.
There are opportunities to minimize markdowns with weather analytics during pre-season planning and allocation processes, as well as, during the selling season. First, when retailers plan the next season or year they must correct the weather bias or variability embedded in past sales performance. By deweatherizing last year’s sales a retailer has visibility into when favorable weather conditions exaggerated sales or unfavorable conditions deflated sales. In situations where prior sales are inflated and the positive weather environment doesn’t repeat the next year, retailers often end up with excess inventories that need to be marked down certain locations.
In-season, there is another opportunity to proactively manage markdowns when a retailer considers expected weather impacts to either delay markdowns for a period of time or reduce the depth of markdowns (e.g. 30% off instead of 50% off).
Perishable shrink: Given the amount of short shelf life perishable products on their shelves, food retailers face the challenge of balancing availability with shrink/waste costs. Erring too far on the side of on-shelf availability may ensure high service levels but it can significantly impact profit. On average, grocers lose about 5% of total sales in fresh categories due to products becoming unsaleable due to quality or expiration dates.
Using store-level, weather-informed replenishment, grocers typically decrease waste by 10-35% in fresh categories from produce to fresh meats. The large improvements are achievable since most replenishment processes and systems rely heavily on historical trends and/or the most recent sales volumes. Leveraging weather insights that adjust replenishment for the weather-based demand changes expected to happen in the coming days or week, grocers can do a better job reducing inventories where demand will be decreasing from recent peaks without risking lost sales due to stockouts.
The above inventory-related examples illustrate how a key market-level factor called the weather offers a proven way to tap into the potential of “localization” and the resulting financial benefits.
Other areas where weather analytics help retailers with expenses include labor (identify where hours can be trimmed), expedited freight/storage/handling costs (avoid costs of moving product), and digital advertising (don’t allocate spend where unfavorable weather makes conversions unlikely).
Oracle Retail Blog
By: Giuseppe Rapisarda, Oracle Retail Supply Chain Solution & Strategy Director
Did you know roughly 5% of a retailer’s total sales are driven by fluctuations in the weather? We are all affected by the weather. Every single day of the year, the weather has a material impact on us, especially in the winter. It affects our mood and it influences how we act. As Milli Vanilli once lip synched, blame it on the rain.
As seasons change, shopper behaviours change and retailers must tap into weather-driven demand patterns to help inform inventory decisions and demand forecasting to predict what shoppers want, where they want it, and when.
With the right tools and retail solutions, retailers can easily understand, interpret, and incorporate weather-driven demand as an integral part of business strategy and inventory planning. I teamed up with Planalytics, a global leader in business weather intelligence, to discuss how incorporating weather-driven demand can help improve forecast accuracy, increase inventory availability, and reduce out-of-stocks.
Weather data is not weather-driven demand
The fundamental truth is that weather data is not the same as weather-driven demand. While many companies have tried to integrate weather data into their demand forecasting operations, it hasn’t been effective. Why? Weather data is subjective, emotional, and complex, and in many cases, it requires expert translation. Unlike weather-driven demand, weather data doesn’t quantify weather’s impact and it can be challenging to scale, making it less effective.
Weather-driven demand, on the other hand, is quantifiable. At its core, weather-driven demand measures the impact of weather on consumer behaviour. It is undeniable that weather impacts what we do, and ultimately can affect consumer demand and buying behaviour. Not only can weather-driven demand help “de-emotionalize” business performance actions, but it is also easier to scale and understand.
Demand reigns supreme
Weather-driven demand data can easily be turned into business value when coupled with Oracle Retail’s solutions. Here’s how. Combine it with a modern attribute-based demand decomposition approach to drive a radical change to the predictive model using next-generation demand forecasting.
The key principle of demand decomposition is straightforward – look for patterns using the actual data of a single SKU at a single location and use the information of similar SKUs and similar locations grouped by attributes. The rate of sales, promotion and price effects, and seasonality all impact consumer demand, and each component is calculated at a different level of attribute aggregation. The embedded machine learning (ML) algorithms select the best attributes and exchange information to produce a statistically stable prediction that is seamlessly merged into the final forecast.
Replenishment is key
A key aspect of weather-driven demand shows up in the replenishment process. Leveraging weather information, we can automatically adopt placement, display, and replenishment parameters, further increasing the value of having a more precise forecast. The number of parameters needed to drive a replenishment system is enormous, and they are continually changing due to events such as the weather and more recently, the pandemic. With Oracle Retail Demand Forecasting, companies can define the strategies and write rules that manage each business scenario. The system will enforce the rules and automatically set the parameter values.
Research shows that 47% of respondents list out-of-stock merchandise at the top of their list for a bad shopping experience and 63% are unwilling to wait for an item to be back in stock before trying another brand. A lack of inventory is the fastest way for retailers to lose loyal customers, according to Oracle’s consumer survey.
By incorporating a weather-driven demand strategy into a business model, along with a modern demand forecasting solution, retailers can better manage inventory levels. When the right quantities of products are in the right locations at the right time consumers have a positive brand experience, sales increase, and a retailer’s overall service is improved.
Because at the end of the day, you want to say “girl, you know it’s true.”
Planalytics is a proud Board Member of, and is participating at this year’s Global Retailing Ideas Summit 2021 from Wednesday, April 28 – Friday, April 30, 2021.
If you are interested in learning more or would like to schedule a time to meetup online during the conference, please contact firstname.lastname@example.org.
Sponsored content by Planalytics
• Minimizing lost sales – and potentially lost customers – due to stockouts is more critical than ever as store traffic trends evolve and competitive alternatives expand.
• The weather affects consumers and their purchasing decisions on a daily basis; no other external variable shifts store-level sales trends as immediately, frequently, and meaningfully.
• Weather analytics improve forecast accuracy in planning, allocation, and replenishment processes and enable retailers to better align inventories with consumer demand.
High levels of customer satisfaction are critical to protecting and growing market share, and nothing puts this in jeopardy more than empty shelves or clothes racks. Retailers can’t afford to miss opportunities to capture sales and to earn shopper loyalty. It has never been easier for customers to go elsewhere to get what they need.
Improving availability needs to be a top priority, but this goal must be pursued in a cost-effective way.
When allocating product ahead of the selling season, store-based retailers want each location to have enough stock to meet demand over time but also want to avoid sitting on costly, unproductive inventory. This is no easy task and when dealing with seasonal merchandise, using the prior year’s sales as a guide often leads to mismatches between market-level demand and available inventories. Some locations miss sales while others sit on excess stocks that eventually may need to be marked down or moved.
In businesses where replenishment decisions are made regularly, demand forecasts need to account for not just what recent sales trends have been but also how purchasing patterns will be shifting going forward. Retailers need to smartly increase stocks ahead of demand spikes, while safely trimming inventories where demand is falling (especially in sectors like grocery where limited shelf life perishables can drive up waste costs).
Don’t overlook a key piece to the ever-changing demand puzzle
Many factors go into what a shopper wants to buy and when they want to buy it. But there is one very influential external variable that too many retailers are still ignoring – the weather.
Demand for all sorts of consumer products – from food and beverages to clothing to items for our homes, gardens, cars and more – varies based on the conditions outside. And the weather never stops changing! This brings challenges to planning because year-to-year the conditions that influence sales rarely repeat. So retailers –those with stores and purely online players – often find that plans that rely heavily on the prior year’s sales often miss the mark. This mistake of “chasing the weather” also affects nearer-term replenishment forecasts, as the favorable conditions supporting sales or the unfavorable conditions suppressing sales, change daily.
Retailers that do not account for the impact of weather are unintentionally building error into plans and demand forecasts. The good news is that precise weather-based demand analytics can be operationalized at scale and integrate with a retailer’s existing technology solutions and/or processes. However, companies should not fall into the trap of assuming that weather data (e.g. temperatures, rainfall totals, etc.) and forecasts will bring the demand forecast accuracy improvements needed to broadly grow sales and profit. The weather’s impacts need to be translated into category- or product-level units in order to make adjustments to plans or automatically modify replenishment system outputs in a systematic, scalable, and repeatable way.
Weather-driven demand metrics, developed through multi-year analyses of actual sales by product/location/time period and corresponding weather conditions, transform weather data into something quantifiable and actionable. With data-driven visibility into how the weather affects purchases, retailers have a powerful way to optimize inventories and improve availability which leads to increased sales and happier shoppers.
Improve forecast accuracy and capture more sales
Whether it is pre-season planning and allocation or in-season replenishment, weather analytics can highlight both when and where sales opportunities and risks for product categories are likely to arise. Quantifying those weather-driven opportunities and risks in unit-based volumes improves a retailer’s forecast accuracy, and for certain products and time periods, those accuracy gains can be as high as 30%.
Reducing forecasting error means inventories are better aligned to consumer demand and this leads to improved availability and fewer lost sales. By applying weather analytics across the business, retailers can add up to a 2% to total topline sales, with much larger gains for specific products and locations. The additional sales and better optimized inventories can also boost profits by 3-5%.
Retailers must capitalize on sales opportunities whenever possible or risk losing customers and market share. Below are a couple of product-specific examples where companies were able to see and take advantage of opportunities highlighted by weather-driven demand analytics:
• An apparel chain reduced winter boot and accessories inventory by 60% after pushing products into markets where demand spiked due to favorable late-season weather.
• A DIY retailer reduced out-of-stocks at distribution centers by 25% without increasing inventory levels.
• A supermarket chain captured over $50k in incremental sales in a fresh category over just a 3-day period by increasing replenishment volumes into markets where the weather would be positive for sales.
For many retailers, optimizing inventories to account for weather impacts remains a great untapped opportunity to improve performance. Retailers would be hard-pressed to find an alternative approach to revenue growth which allows them to extract more from existing technology investments with minimal technical effort to implement. The value return materializes quickly, usually within weeks.
By: Thad Rueter
As if the pandemic and mass vaccination efforts were not enough for food retailers in early 2021, now comes the impacts of extraordinarily frigid and snowy weather across many parts of the country. . . .
. . . The importance of retailers keeping track of winter weather — and crafting appropriate responses — was driven home late last year via a National Retail Federation interview with Evan Gold, EVP of global partnerships and alliances for business weather intelligence firm Planalytics. Gold has more than 20 years’ experience in retail and wholesale, working at Macy’s and LakeWest Group before joining Berwyn, Pennsylvania-based Planalytics in 2005. He spoke with Washington, D.C.-based NRF about the ways weather impacts retail and the supply chain, and the discussion serves as a reminder that a virus isn’t the only wildcard that retailer face this year.
In the longer term, retailers and consumer will turn to technology to deal with climate variations, especially when it comes to supply-chain issues.
“The customer has more access to information at their fingertips and the ability to shop whenever they want,” Gold said. “As the weather becomes more volatile, the shopper is shopping based on need. If you layer in weather and can have an idea of what they’re going to buy, or do more prescriptive analytics, and be able to market and advertise into that, they’re more likely to buy from your brand.”