With hundreds of online retailers and thousands of products to select from, an average modern-day shopper compares pricing across many e-commerce websites quickly before settling for the lowest-priced alternatives. So, retailers had to execute millions of changes in prices daily in this never-ending race to become the lowest priced without losing any possible margin.
Recognizing, categorizing, and matching products is the initial step to comparing prices across different websites. However, there needs to be a correction in how products get represented across various e-commerce websites; this procedure is moderately complex.
Let’s go through an example:
What’s required here is a price intelligence solution that initially matches products in many websites accurately and swiftly and then allows auto-tracking of competitor price data constantly.
Many challenges are there with mandatory solutions available in the market – the major one is that they are not working appropriately. It’s like complying with the procedure of getting actionable data that assists retailers in acquiring competitive advantages to do that in reflection.
Here are the different solution types that we get in today’s market:
The competitive price intelligence solutions of Actowiz Solutions are specially designed to assist retailers in achieving competitive advantages precisely by offering timely, accurate, and actionable price insights allowed by matching products. We offer retailers access to detailed price data on millions of competitor products as often as they want.
Our technology stack primarily includes the following.
At Actowiz Solutions, we aggregate data from various web resources across composite web environments – constantly with higher accuracy. Being in this industry for a long, we’re used to a lot of data that we can utilize to train product-matching platforms.
Our datasets comprise data from millions of products collected from many verticals and geographies in retail. These datasets have hierarchically organized data based on the retail taxonomy. There’s information like categories and subcategories; at top levels, we have essential product information like titles, descriptions, and other relationships. Our architectures of Machine Learning with a semi-automated data-building system, improved by a skilled QA team, assist us in interpreting the needed information and making labeled datasets with exclusive tools.
Product matching at Actowiz Solutions is made through a combined platform that uses image and text recognition capabilities to precisely identify comparable SKUs with millions of products and e-commerce stores. Products also get classified depending on their structures, and a standardization layer is intended based on different image or text-based attributes. We use a collective deep learning architecture personalized to Computer Vision problems and NLP precise to us.
While technically a vital part of a product matching procedure, we use a semantics layer and deserve specific mentions because of its influential capabilities.
We use customized and state-of-the-art word representation methods like BERT, ELMO, and Transformer for capturing intensely contextualized text having better accuracy. An intra-attention or self-attention mechanism studies the association between the words in the question and the last parts of a description.
Image data processing begins with object recognition to classify any product area of interest. Then we use deep learning architectures like Inception-V3, ResNet, and VggNet, which we have accomplished using billions of categorized images. Then, we use different pre-processing methods like face removal, skin removal, flexible background removal, image quality improvement, and scrape image signatures through Machine Learning and deep learning-based algorithms to recognize products exclusively across millions of indexed products.
Lastly, we competently allocate billions of images from different stores for quick access and facilitate searches on a vast scale utilizing our image-matching engines.
In situations where the confidence score of machine-driven matches is lower, our team of Quality Assurance (QA) experts validate the output.
Our team does things like:
We’ve created a self-improvement feedback loop that improves with time. This procedure helps us rapidly match products at a considerable scale with high accuracy (usually more than 95%). Our system has gathered knowledge over years of our operations that will be hard for anybody to repeat.
When the matching procedure is completed, the pricing is aggregated frequently, allowing retailers to improve their pricing constantly. Usually, pricing insights are characteristically consumed using our SaaS-based web portal that includes reports, dashboards, and visualizations.
Instead, we can take part with interior analytics platforms using APIs or produce and provide regular spreadsheet reports per the customers’ preferences.
There are numerous advantages of our solutions. Detailed pricing improvement opportunity-associated insights produced appropriately empower retailers to meaningfully improve their competitive position across product types, categories, and brands, with the ability to influence their pricing perception amongst consumers. All these insights, if used at high granularity in the long run, can assist in maximizing revenue using price optimization on a larger scale.
Our solutions also help in driving process-based and operational optimization for retailers. These modifications assist them with better alignment to efficiently take a data-driven approach to price and help them achieve cleverer retail operations worldwide.
All these wouldn’t be possible if a product matching procedure integral to this system were expensive, unreliable, or inefficient.
If you want to know more about Actowiz Solutions’ proprietary product matching platforms and their advantages to brands and e-commerce businesses, contact Actowiz Solutions now!
You can also reach us for all your web scraping services and mobile app scraping service requirements.
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Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.
Find Insights Use AI to connect data points and uncover market changes. Meanwhile.
Move Forward Predict demand, price shifts, and future opportunities across geographies.
Industry:
Coffee / Beverage / D2C
Result
2x Faster
Smarter product targeting
Operations Manager, Beanly Coffee
✓ Competitive insights from multiple platforms
Industry:
Real Estate
Result
2x Faster
Real-time RERA insights for 20+ states
Data Analyst, Aditya Birla Group
✓ Boosted data acquisition speed by 3×
Industry:
Organic Grocery / FMCG
Result
Improved
competitive benchmarking
Product Manager, 24Mantra Organic
✓ Real-time SKU-level tracking
Industry:
Quick Commerce
Result
2x Faster
Inventory Decisions
Aarav Shah, Senior Data Analyst, Mensa Brands
✓ 28% product availability accuracy
✓ Reduced OOS by 34% in 3 weeks
Industry:
Quick Commerce
Result
3x Faster
improvement in operational efficiency
Business Development Lead,Organic Tattva
✓ Weekly competitor pricing feeds
Industry:
Beverage / D2C
Result
Faster
Trend Detection
Marketing Director, Sleepyowl Coffee
Boosted marketing responsiveness
Industry:
Quick Commerce
Result
Enhanced
stock tracking across SKUs
Growth Analyst, TheBakersDozen.in
✓ Improved rank visibility of top products
Real results from real businesses using Actowiz Solutions
In Stock
₹524
Price Drop + 12 min
in 6 hrs across Lel.6
Price
Drop −12 thr
Improved inventory
visibility & planning
Actowiz's real-time scraping dashboard helps you monitor stock levels, delivery times, and price drops across Blinkit, Amazon: Zepto & more.
✔ Scraped Data: Price Insights Top-selling SKUs
"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"
✔ Scraped Data, SKU availability, delivery time
With hourly price monitoring, we aligned promotions with competitors, drove 17%
✔ Scraped Data, SKU availability, delivery time
"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"
✔ Scraped Data, SKU availability, delivery time
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