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[locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array ( [0] => en ) [validAttributes:protected] => Array ( [0] => confidence [1] => geonameId [2] => isInEuropeanUnion [3] => isoCode [4] => names ) ) [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object ( [record:GeoIp2\Record\AbstractRecord:private] => Array ( ) [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array ( [0] => en ) [validAttributes:protected] => Array ( [0] => confidence [1] => geonameId [2] => isInEuropeanUnion [3] => isoCode [4] => names [5] => type ) ) [traits:protected] => GeoIp2\Record\Traits Object ( [record:GeoIp2\Record\AbstractRecord:private] => Array ( [ip_address] => 216.73.216.115 [prefix_len] => 22 [network] => 216.73.216.0/22 ) [validAttributes:protected] => Array ( [0] => autonomousSystemNumber [1] => autonomousSystemOrganization [2] => connectionType [3] => domain [4] => ipAddress [5] => isAnonymous [6] => isAnonymousProxy [7] => isAnonymousVpn [8] => isHostingProvider [9] 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=> Array ( [0] => averageIncome [1] => accuracyRadius [2] => latitude [3] => longitude [4] => metroCode [5] => populationDensity [6] => postalCode [7] => postalConfidence [8] => timeZone ) ) [postal:protected] => GeoIp2\Record\Postal Object ( [record:GeoIp2\Record\AbstractRecord:private] => Array ( [code] => 43215 ) [validAttributes:protected] => Array ( [0] => code [1] => confidence ) ) [subdivisions:protected] => Array ( [0] => GeoIp2\Record\Subdivision Object ( [record:GeoIp2\Record\AbstractRecord:private] => Array ( [geoname_id] => 5165418 [iso_code] => OH [names] => Array ( [de] => Ohio [en] => Ohio [es] => Ohio [fr] => Ohio [ja] => オハイオ州 [pt-BR] => Ohio [ru] => Огайо [zh-CN] => 俄亥俄州 ) ) [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array ( [0] => en ) [validAttributes:protected] => Array ( [0] => confidence [1] => geonameId [2] => isoCode [3] => names ) ) ) )
country : United States
city : Columbus
US
Array ( [as_domain] => amazon.com [as_name] => Amazon.com, Inc. [asn] => AS16509 [continent] => North America [continent_code] => NA [country] => United States [country_code] => US )
In consumer brands, the digital marketplace presents unprecedented opportunities for customer engagement and market expansion. Within this dynamic landscape, incorporating Digital Shelf Analytics becomes pivotal in a brand's eCommerce strategy. This cutting-edge technology provides crucial insights into a brand's visibility, encompassing organic and paid aspects on various marketplaces. It delves into essential facets such as content quality, pricing strategies, promotional initiatives, and product availability. By emphasizing concepts like Digital Shelf Analytics, ROI business, eCommerce scraping services, retail analytics, and retail data collection, brands can effectively utilize these insights to understand their competitive positioning and elevate their overall market performance.
Despite the challenges many brands face in understanding whether insights from the digital shelf translate into actionable strategies that drive tangible business impact and ROI, there is evidence that effectively leveraging these insights can lead to significant, measurable benefits.
The crucial question remains: Does Digital Shelf Analytics live up to its promises? At Actowiz Solutions, we have collaborated with numerous brands, empowering their eCommerce growth through digital shelf analytics. This article will explore these insights, revealing the concrete and quantifiable results that brands can attain through their investments in digital shelf analytics.
Digital Shelf Analytics is a robust system that analyzes key performance indicators (KPIs) related to the digital shelf. This system provides brands with precise recommendations to strengthen these KPIs and monitor improvements over time. The following concisely explains digital shelf KPIs and the impact areas they are expected to influence.
Accurate and timely insights into product availability are essential for brands to streamline large-scale replenishment processes, exerting a significant influence on sales and establishing a robust correlation between product availability and revenue. Through the utilization of Digital Shelf Analytics, purchasing and replacement teams can configure notifications to swiftly identify low or out-of-stock items, facilitating prompt corrective action. This capability extends to specific ZIP codes or individual stores. Additionally, product availability plays a pivotal role in determining a brand's Share of Search and search rankings, as online marketplaces prioritize displaying in-stock products among the top results.
In the digital realm, product visibility is paramount – if a product isn't visible, does it exist? With 70% of consumers never venturing beyond the first page of search results on major online marketplaces, a brand's product visibility for relevant search keywords, particularly on the first page, significantly influences awareness metrics. Enter the concept of Share of Search, akin to securing prime shelf space in a physical store. Leveraging digital shelf insights and benchmarking against category leaders, Share of Search ensures that your products garner substantial attention on the digital shelf.
In the competitive landscape of a crowded marketplace, creating captivating product descriptions and visuals is like providing your products with a powerful megaphone. Elevating content quality, encompassing product names, titles, descriptions, and images, empowers brands to ascend the search result rankings, resulting in heightened visibility and, consequently, increased sales.
The power of public opinion is significant, as research has shown that a single positive review can result in a 10% boost in sales. Additionally, accumulating multiple favorable reviews can push a product to a 44% higher trajectory. This connection between ratings and sales is unsurprising, as each step up the rating scale can lead to significant revenue growth.
While anticipating a correlation between these key performance indicators (KPIs) and downstream impact metrics like impressions, clicks, and conversions, we delved into this connection through an analysis of real-world data. We precisely monitored digital shelf KPIs for our client and scrutinized the enhancements in these metrics.
It's important to note that not all observed impact areas can be solely attributed to enhancements in digital shelf KPIs. Nevertheless, a strong and clear correlation does exist. The following section presents an in-depth case study that sheds light on the results of this analysis.
Join us as we explore the journey of a well-known consumer packaged goods (CPG) brand that specializes in baked food and desserts. Through their experience, we aim to showcase the transformative effects of our Digital Shelf Analytics products suite. In the time period from August ‘22 to July ‘23, the brand actively utilized various critical components of Digital Shelf Analytics used for Amazon. These modules, which include Share of Category, Share of Search, Availability, Reviews, Ratings, and Content Audit, served as essential digital shelf key performance indicators (KPIs), significantly shaping the brand's performance at different stages of the buyer's journey.
The typical buyer's journey unfolds in three distinct stages:
Awareness: Shoppers explore various product options displayed on category and search listing pages, gaining an initial understanding of the available choices.
Consideration: Shoppers narrow their selections, evaluating a few products more closely as they move closer to a purchase decision.
Conversion: In the final stage, the shoppers make their final product choice and complete the purchase.
Now, let's delve into the data to comprehend how digital shelf KPIs played a pivotal role in driving tangible ROI on Amazon for the brand across these stages of the buyer's journey.
In the first stage, our aim is to increase the visibility of the product and create brand awareness. To achieve this, we focus on improving the Share of Search and the Share of Category. Our client has seen consistent and incremental improvements in their Share of Search and Share of Category over the analyzed period. This has been possible through the strategic implementation of various tactics such as product sponsorship, content enhancement, price optimization, and promotional initiatives. The chart below illustrates the improvements made by our client within the top 20 ranks of each listing page.
This increased Share of Search and Share of Category directly results in enhanced product discoverability, as highlighted by the notable surge in impressions in the chart below.
During the consideration stage, shoppers refine their product choices based on factors such as average rating, the number of ratings, price, product title, and images. This emphasizes the critical importance of brands creating meticulously detailed product content and accumulating significant ratings.
The following chart depicts the year-long trend in average ratings and the number of ratings, showcasing a consistent and positive improvement over time.
The improvements in both the number of ratings and the average rating exert a direct and positive influence on product consideration. Consequently, this has resulted in a discernible year-over-year increase in page views, as depicted in the chart below.
These enhancements are likely inclined by the overall improvement of content quality that is given distinctly in the section given below.
As buyers move to the next stage, they reach a crucial point of purchase. Several factors influence this decision, including product availability, content quality, and the quality of reviews that reflect customer sentiment.
Our client utilized our Availability insights efficiently, considerably reducing the possibility of probable out-of-stock scenarios and better replenishment rates. This improvement is highlighted in the chart below. The same chart also demonstrates an improvement in content quality, as measured by the alignment of content on Amazon with the brand's ideal content standards.
Below, you'll discover the year-over-year conversion rate growth for the Amazon brand. This metric is the ultimate gauge of business impact, directly translating into heightened brand revenue.
As revealed by the data, the growth in critical digital shelf KPIs collectively exhibited a robust correlation with impressions, page views, and conversion rates. It's crucial to acknowledge that the impact of each KPI cannot be viewed in isolation, as they often exhibit interdependence. For instance, enhancements in content and availability could elevate Share of Search, while accurate content contributes to more positive customer feedback. Brands should adopt a holistic optimization approach to digital shelf KPIs to generate sustained business impact.
Following the integration of digital shelf analytics, the outcomes were self-evident. Sales consistently surpassed the previous year's records month after month. As depicted in the chart below, the meticulous application of Actowiz Solutions' recommendations resulted in a noteworthy 8.5% year-over-year increase in sales, leaving a lasting imprint on the brand's eCommerce success.
Digital Shelf Analytics is a powerful tool that can help brands achieve unparalleled online success, from increasing product visibility to boosting conversion rates. While it's not yet possible to create a direct connection between sales revenue and Digital Shelf Analytics, there is a clear correlation that should not be ignored. By using digital shelf KPIs, brands can optimize their eCommerce performance across all stages of the buyer journey. Therefore, it's crucial for brands to work with the suitable partner and leverage digital shelf insights to perfect eCommerce tactics and strategies.
However, the eCommerce arena is constantly changing, and you can learn so much about how every digital shelf KPI affects brand performance online.
If you want to see your brand succeed in eCommerce, contact us today to learn more about how Digital Shelf Analytics can help you drive higher sales and market share. You can also reach us for all your mobile app scraping, instant data scraper and web scraping service requirements.
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