All posts by Tara McAdams

Seamless integration of predictive weather-driven demand analytics

By: Jim Lewis, CEO, Enhanced Retail Solutions


One of the most common project requests we get is integrating 3rd party information or research with a client’s POS data and forecast. For example, a client who manufactures home products combines the forecast of new home sales, U.S. Census demographics with historic seasonality to help them improve the predictability of sales. Other examples include integrating gas prices, market growth data, consumer confidence, weather, and industry specific indices. Adding additional layers of data can vastly improve decision making and lead to more productive inventory management. It also enables a client to track their own growth and sales trends against their specific industry trend. However, the challenges of obtaining and integrating third party data is extremely cumbersome and discourages most companies from attempting it.

Luckily, there are some cases where the hard work of obtaining and making 3rd party data useful has been streamlined. For example, our partnership with Planalytics offers seamless integration of predictive weather-driven demand analytics directly into the ERS forecast. Measuring how changes in the weather increase or decrease demand enables companies to better understand performance, improve forecast accuracy, and manage inventory levels over time. And because Planalytics’ weather analytics are available by geographic region, it can easily be integrated at scale with ERS’ store level allocation solutions including VMI (Vendor Managed Inventory). This enables our clients to offer their retail partners more robust and efficient planning by lowering carrying costs and freeing up more working capital. A win-win for both manufacturer and retailer. See an example here.

Another example of seamless integration is U.S. Census demographics built into ERS’ Best Practices Planning Toolkit. It enables a client to study their product’s performance by geographic region and the age, education, income, and ethnic makeup of those communities. Because it uses aggregate rather than transaction data, there are no personal privacy issues. It is a great tool for testing new products and aligning allocation quantities with each store. A client can review at any level- size, color, style, brand so they can tailor assortments in the most productive manner. All of which reduces risk and ensures the right products are at right places at the right time.

Integrating 3rd party data with POS and Forecasts is a real-world example of the benefits of “big data”. The availability of tools and affordable pricing make data-packed automated forecasts a no-brainer against manual spreadsheet-based forecasting.

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The Product Demand Index: A Powerful Predictive Analytic that Helps Advertisers Understand “Consumer Context” and Improve Returns

The move to more contextually-based audience selection for display ads continues to accelerate. And as businesses face the challenge of replacing cookie-driven audience targeting, marketers are looking for proven ways to create relevant advertising that drives purchases and brand loyalty.

Contextual targeting has emerged as a powerful solution, but it’s important to explore different types of contextual targeting. Although page context has certainly been an option for targeting, understanding the broader consumer context is even more powerful. One type of advanced contextual targeting, geo-contextual targeting, allows advertisers to target audiences based on the demand generated by the context of a consumer’s immediate environment.

Peer39 partners with Planalytics

Planalytics and Peer39 have partnered to bring geo-contextual targeting to programmatic ad buying at scale. Through Peer39’s Contextual Data Marketplace, businesses leverage Planalytics’ product demand index to identify optimal times and locations to advertise in-market categories.

Knowing when to spend and when not to spend, knowing what product to feature, knowing which markets and individuals will be most receptive to messaging are critical to increasing clicks and conversions. “Context is King” when it comes to consumer spending and advertisers that leverage the product demand index on Peer39’s Contextual Data Marketplace can dramatically improve their returns.

Planalytics has seen major consumer industry clients improve performance significantly. For example, one mass merchant client saw an average sales increase of 8% where the analytics were used to target specific markets with specific products. In another example, a client used the analytics to select audiences and saw ROAS increases that were 3 to 4 times the gains captured with traditional cookie-based behavioral targeting.

Planalytics provides businesses with a proven and measurable return on investment by applying advanced statistical methods and machine learning, mountains of sales data, and years of unmatched retail demand expertise to the most omnipresent external localized influencer of purchasing – the weather.

The importance of weather in contextual targeting

The weather is the most consistent and impactful external environmental driver of demand in the consumer economy. Planalytics’ Product Demand Index goes far beyond triggers based on temperatures and other meteorological conditions, and instead, puts a consumer context around the weather.

Understanding and acting on this context has been consistently and measurably effective. When combined with promotions or layered on top of other types of audience targeting an observable “synergistic effect” occurs, and the efficacy of both optimizations is boosted.

Advertising in-market products leads to situations where sales were notably higher than the expected promotional lift and weather lift individually suggested. For example, if a digital campaign for soup has historically generated incremental sales of 5% and Planalytics metrics point to an additional 10% boost, a business may see 25% more in sales. This additional 10% over the expected lift is the synergistic effect of targeting an audience with a product message while the in-market product “tailwind” is also contributing to demand.

Accessing the Planalytics’ product demand index through Peer39’s Contextual Data Marketplace allows businesses to Identify ambient-driven in-market categories for programmatic ad buying and take advantage of opportunities where this synergistic effect can inflate returns.

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4 ways restaurants leverage weather analytics

Sales transactions, from dine-in to delivery to drive-thru, are affected by the weather every day. Soaring temperatures, rainy days, icy roads, and other external conditions directly impact the number of people that will come through the doors or order through an app. The weather also influences customers’ food and beverage choices.

Restaurants can boost sales by taking advantage of favorable weather periods and manage costs when unfavorable conditions reduce demand. Data-driven visibility into the weather’s impact allows operators to more effectively target digital marketing, better align staffing with demand levels, and adjust food orders to ensure availability while managing perishable waste costs.

Companies need demand analytics, not just weather forecasts, to understand and consistently address a constant driver of sales volatility. Translating temperature readings and precipitation amounts into business metrics (e.g. percent/revenue/volume changes) makes it possible for companies to successfully incorporate weather impacts into existing processes, technology solutions, and reports.

It’s Monday morning and management is wondering why sales were so sluggish in the Northeast when performance was noticeably stronger in other regions. In another meeting, the marketing team is having trouble figuring out the effectiveness of a digital campaign with return on advertising spend (ROAS) varying wildly depending on the market or the week. And, on an investor call, an analyst is asking for the reasons why results did not match up with previously provided comp sales guidance.

There’s a very good chance the common thread running through all of these situations is an everyday factor that is too often overlooked or misunderstood – the weather. Each day, consumers make decisions on what activities to pursue, whether to venture out or stay home, and what to spend money on based on the conditions outside.

While it is true that there are many external drivers a business faces – the economy, consumer confidence, and of course, something as impactful as COVID-19 – these large-scale underlying factors tend to develop over time and evolve slowly. Weather is different. In fact, no other external factor changes consumer demand as frequently, immediately, and meaningfully as the weather.

The good news is that with the right analytics, the weather’s impacts can be measured and managed by restaurant chains. Weather-driven demand analytics isolate how much the weather impacts sales, from a total business perspective down to specific channels (e.g. food delivery vs. dine-in, etc.) and even down to the item-level (e.g. soups vs. salads, etc.). In our experience working with leading chains, these are the weather analytics that are most commonly leveraged by restaurants:

1. Evaluating performance from a weather-adjusted perspective

The weather influences consumer spending on a daily basis. Therefore, any consumer-based business, including restaurants, really needs to quantify the positive and negative impacts of weather to clearly understand performance.

Using analytics to measure the weather’s impact in a consistent and systematic manner enables “apples to apples” comparisons. For example, if unadjusted sales are up 5% in Texas and down 3% in Florida, it appears that one market is outperforming the other. However, if Texas was supported by a favorable weather backdrop calculated to be +7% and Florida faced a more negative situation where the weather impact was -10% a completely different conclusion emerges. From a weather-adjusted standpoint, Texas is -2% while Florida is actually +7%.

By removing the weather biases from the results, restaurants can better gauge true performance. Sales results are an obvious place where a “weather neutral” perspective is helpful. In addition, companies will benefit by analyzing other areas by using this same approach. For example, why did a promotion perform well in the first week of the month, but not the second? Why was ROAS on our Facebook ads twice as high in the Midwest as it was in California?

Weather-driven demand analytics put a precise number on how the weather impacted sales or other business metrics, and this allows restaurants to identify exactly how much the weather influenced performance versus other factors.

2. Factor in upcoming weather impacts to support sales and manage costs

Weather-driven demand outlooks that factor in near-term meteorological forecasts help businesses proactively manage upcoming opportunities and risks. For example, knowing that there will be stronger demand for salads in key markets over the next week could encourage a company to increase inventories ahead of the sales spike to maintain sufficient availability and avoid lost sales. On the other hand, negative weather-driven demand projections would allow the company to trim orders and minimize waste costs.

3. Optimize digital marketing spend

Weather-driven demand analytics offer a proven way for businesses to increase digital marketing effectiveness and capture market share by putting a consumer context around the weather. Temperature triggers or other meteorological data points are not as effective because they do not account for important regional, temporal, and buying trends and traits. After all, how a consumer reacts to 68◦ F is far from uniform, as the answer is different in Las Vegas than in Louisville; different if it is March or July or October; and different across various products.

One constant Planalytics has seen in our work with clients is that campaigns that overlap with favorable, weather-induced demand lead to a larger-than-expected sales boost. Restaurants can capitalize on this “synergistic effect” by targeting audiences where the weather is creating demand and a product or service is highly relevant to them at that time. For example, a campaign promoting pasta specials may have historically generated incremental sales of 15%. When weather-driven demand metrics point to an additional 10% boost the company saw a 40% jump in sales. This additional 15% over the expected 25% lift is the synergistic effect of targeting an audience while a weather “tailwind” is also contributing to demand.

4. Improve plans by “deweatherizing” historical sales

The benefit of having a weather-adjusted perspective mentioned as the first common use case above has a related and extremely valuable application in planning. Companies unintentionally build error into the next year’s financial or sales plans when the weather volatility that inflated or deflated results are left unadjusted in the forecast baseline. The problem is that they are assuming the weather impacts that occurred in specific markets at specific times of the year will repeat again next year. This rarely happens.

By “deweatherizing” or correcting for positive and negative effects in historical sales, restaurant chains can avoid the trap of “chasing the weather” and the sales impacts that are unlikely to mirror the prior year. This helps companies see when and where opportunities and risks are more likely to arise when planning the year ahead and can inform forward-looking guidance a business gives to investors and stakeholders.

Learn more by visiting Weatherizing a Restaurant Business on the Planalytics’ website.

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Weather-Driven Demand Analytics from Planalytics Now Available on SAP® Store

By integrating with SAP Analytics Cloud and SAP Customer Activity Repository, Planalytics’ solution helps businesses stay ahead of changing demand and increase sales and profitability

Berwyn, PA — June 7, 2021 — Planalytics, Inc., an SAP® partner in the SAP PartnerEdge program, today announced that its Weather-Driven Demand Analytics solution is now available on SAP® Store, the online marketplace for SAP and partner offerings. The solution utilizes demand analytics to factor in the impact of the weather – the most consistent and impactful external environmental driver of consumer demand – and integrates this information into existing SAP solutions including SAP Customer Activity Repository and SAP Analytics Cloud. Within 90 days, businesses can improve and automate core processes at scale, capture forecast accuracy improvements and begin to see the following benefits:

● Increased topline revenue by up to 200 basis points
● Growth of profit by 2-6%
● Reduced perishable waste up to 35%

“The ability for businesses that use SAP solutions to directly and more easily access and integrate predictive analytics will help them proactively sense changes in demand and provide a clearer picture of performance,” said Frederic Fox, Planalytics CEO.

By integrating with SAP Analytics Cloud and SAP Customer Activity Repository, Planalytics’ solution will help businesses more accurately account for weather-based sales variability and understand overall business performance. In addition, forward-looking projections will enable businesses to stay a step ahead of shifting demand trends. By better aligning inventory with consumer demand, companies can improve service levels, capture sales and market share, and improve profitability.

SAP Store, found at store.sap.com, delivers a simplified and connected digital customer experience for finding, trying, buying and renewing more than 1,800 solutions from SAP and its partners. There, customers can find the SAP solutions and SAP-validated solutions they need to grow their business. And for each purchase made through SAP Store, SAP will plant a tree.

Planalytics is a partner in the SAP PartnerEdge® program. As such, it is empowered to build, market and sell software applications that supplement and build on SAP software and technology. The SAP PartnerEdge program provides the enablement tools, benefits and support to facilitate building high-quality, disruptive applications focused on specific business needs – quickly and cost-effectively. The program provides access to all relevant SAP technologies in one simple framework under a single, global contract.

ABOUT PLANALYTICS

Planalytics Inc. delivers demand sensing analytics to retailers, consumer goods manufacturers, restaurants, and service companies. By applying advanced statistical methods and machine learning, mountains of sales data, years of unmatched retail demand expertise to the most omnipresent external influencer of purchasing – the weather, Planalytics provides businesses with a proven and measurable return on investment. Leading consumer brands across the globe rely on Planalytics weather-driven demand metrics to improve planning accuracy and optimize inventory allocation, replenishment, digital advertising, and other core activities. Learn more by visiting www.planalytics.com.


Any statements in this release that are not historical facts are forward-looking statements as defined in the U.S. Private Securities Litigation Reform Act of 1995. All forward-looking statements are subject to various risks and uncertainties described in SAP’s filings with the U.S. Securities and Exchange Commission, including its most recent annual report on Form 20-F, that could cause actual results to differ materially from expectations. SAP cautions readers not to place undue reliance on these forward-looking statements which SAP has no obligation to update and which speak only as of their dates.

SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE in Germany and other countries. Please see https://www.sap.com/copyright for additional trademark information and notices. All other product and service names mentioned are the trademarks of their respective companies.

For more information, press only:

David Frieberg, VP of Marketing, Planalytics: dfrieberg@planalytics.com

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Planalytics Projects Below-Trend US Corn Yields But Above Last Year’s Crop

First of Eight Rounds of Satellite-Based Crop Assessments Just Released

BERWWN, PA, June 4, 2021 — “Weather thru June could play a greater role than usual in establishing baseline expectations for the 2021 US corn crop.” This is one of the observations from Planalytics’ initial GreenReport Corn Yield Forecasts that utilize satellite imagery to measure current crop vigor in combination with historic yields.

Produced in collaboration with TerraMetrics Agriculture, Inc., Planalytics initial national corn yield estimate of 174.3 bushels per acre represents an increase of 2.3 bushels over last year’s subpar crop. USDA reported earlier this year the final 2020 yield was 172 bushels per acre. Their May WASDE report predicted a 2021 US corn yield estimate of 179.5 bu/ac.

“This is our 20th year of real-time, satellite-based crop yield forecasting”, stated Jude Kastens, PhD, Research Associate Professor at the Kansas Applied Remote Sensing Program (KARS) located at the University of Kansas. Kastens is senior analyst on the joint Planalytics/TerraMetrics project that includes forecasting yields on a bi-weekly basis for winter wheat, soybeans and five other summer crops in addition to corn. “While we typically observe behavior in our forecasts more or less consistent with early-season USDA crop conditions, this year the discrepancy – our national estimate is 6.1 bushels below trend yield, while USDA crop conditions are well above average – is large.”

With the growing season just getting underway and areas of soil moisture shortage particularly prominent in the Western Corn Belt, the possibility of a dry near-term outlook expanding eastward could impact corn plants at a critical agronomic stage, between emergence and pollination. “Since corn growth is heavily driven by daytime high temperatures, and since much of the Corn Belt recently experienced a week or two or substantially cooler-than-normal temperatures, many fields have been slow to develop,” added Jeffrey Doran, Planalytics Director of Specialized Support and Services. “This may have offset any timing-related early planting advantages and could also account for the average-looking satellite greenness we’ve reported in our weekly GreenReport”.

“The bottom line”, Kastens says, “is that depending on how June weather shakes out, any broad shift toward warmer and drier conditions could have a negative impact on maximum yield potential across a wide area. While it is too early to get alarmed, this certainly is a situation we’ll be keeping an eye on.”

Planalytics biweekly crop yield forecasts are provided are available on an annual subscription basis. For more information, go to www.planalytics.com, or contact Planalytics at 800.882.5881.


ABOUT PLANALYTICS

Planalytics, Inc. (www.planalytics.com) is the global leader in Business Weather Intelligence®. Through advanced weather analysis technologies, planning and optimization solutions, and industry-specific expertise, Planalytics helps companies precisely measure weather-driven impacts and effectively manage the never-ending variability of climate. Leading companies from a wide array of industries use Planalytics to “weatherize their business”, taking advantage of opportunities to increase revenue while deploying strategies to reduce costs and protect margins during periods of risk.

Kansas Applied Remote Sensing (KARS) is a research program of the Kansas Biological Survey at the University of Kansas. The Program was established by the National Aeronautics and Space Administration (NASA) and the State of Kansas to conduct applied research on techniques that enable public agencies and private firms to better utilize data from satellite and air-borne remote sensing systems. Since 1996, KARS and its commercial partners, TerraMetrics Agriculture, Inc. and Planalytics, Inc., have focused research on environmental and agricultural applications of remote sensing technology and the transfer of products and services derived from remote sensing technologies to commercial, governmental, and other end users.

MEDIA CONTACT: Jed Lafferty, Managing Director, Life Sciences, jlafferty@planalytics.com

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Boosting Digital Marketing Returns with Predictive Consumer Demand Analytics

Join Planalytics on June 16th to learn how companies are factoring in a key external driver of consumer purchasing to optimize digital marketing activities and generate better returns.

“Context is King” when it comes to consumer spending and businesses that know when to spend/not spend, know what product to feature, and know which markets and individuals will be most receptive to messaging can improve campaign effectiveness and performance metrics.

No other external variable influences consumer purchasing as immediately, frequently, and meaningfully as the weather. However, meteorological data in a vacuum is not the same – nor nearly as useful and effective – as weather-driven demand analytics. Planalytics puts a consumer context around the weather, creating analytics that companies use to improve digital marketing.

Webinar topics include:

  • Overview of weather-driven demand analytics.
  • Taking advantage of the “synergistic effects” of promoting into favorable weather-based demand situations.
  • Use case examples for email marketing, digital display, and social advertising.

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Predictive Analytics for Retail and Fashion

FIT’s Predictive Analytics for Retail and Fashion Certificate Program is an interactive 6-week course (June 14 – July 26, 2021, skips July 5th) that covers analytics techniques applied to retail and fashion-related industries. The course contains lectures, discussions, and case studies involving analytical techniques that can be applied to retail and fashion business scenarios. Both the analytics and business side of all calculations and techniques will be discussed. How these techniques are used and why they make sense for a business are woven together throughout the course.

You will learn how to analyze demand and retail data and how components such as seasonality, trend, and weather affect the data. You will apply statistical techniques to predict forecasts and measure their accuracy. In an extended case study for weather analytics, you will analyze the effect of weather on business data. For this you will work directly with visiting industry experts from Planalytics.

You will develop the ability to analyze inventory management decisions using the tools of statistics and probability and gain facility in decision making under uncertainty. This course will involve hands-on use of common spreadsheet tools with many specific applications involving demand, seasonality, trend, forecasting, tracking, lost sales, lead time, safety stock, promotions, advertising, pricing, and markdowns. Emphasis will be on common analytical techniques that can be leveraged for any business situation.

Planalytics’ Mohan Anand, Senior Director, Value Engineering and Strategic Analytics and Evan Gold, EVP, Global Partnerships and Alliances are presenting and will be part of the program.

*PLEASE NOTE: this is a Fashion Institute of Technology program.

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