TL; DR: Intelligence Node is with a mission to help retailers compete inside digital economy by profiting data-driven pricing and promoting strategies that boost profits. Using proprietary AI-driven algorithms, your independent data powerhouse compiles remarkably accurate and comprehensive datasets for you to optimize decision-making with lowest upkeep. Ultimately, Intelligence Node’s goal should be to help forward-thinking retailers adapt to a Google-driven environment wherever data-driven pricing and assortment planning isn’t longer optional.
Stores, prepare your eulogies: Classic merchandise planning is basically dead.
According to Sanjeev Sularia, CHIEF EXECUTIVE OFFICER and Co-Founder of Thinking ability Node, digital transformation features rendered dated, intuition-based strategies useless while ushering in a very new era of data-driven rates and assortment planning.
Sanjeev said he along with his co-founders saw the change being released 2012. In response, the team built a tremendous database of retail products that might empower brands to integrate lifecycle pricing inside their merchandising strategies.
“But we planned to do even more, ” Sanjeev explained. “We wanted to supply retailers and brands a new fighting chance — not simply to survive in age Amazon but to thrive within it. The goal was to generate a complete retail and internet commerce solution that would manage everything from pricing for you to assortment. ”
Similar solutions existed available from large consultants, including Mckinsey, BCG, and Bain, along with traditional SaaS players similar to Oracle and SAP. But these lenders relied heavily on internal data and still did not address one critical simple fact: that the consumer could always shop elsewhere.
“That is the hole we plugged by creating Bloomberg-like software package for retail pricing to provide in-depth competitive insights instantly for quality decision-making, ” Sanjeev instructed us.
At a time when pricing decisions are produced in minutes, not days and nights, Intelligence Node aims for you to serve as its customers’ eyes and ears out there.
“We give you the all-inclusive, easy-to-use solution tailored to your category so that you can determine the best rates, assortment, promotion, and sales strategy criteria determined by real-time inventory and credit information, ” Sanjeev explained.
Powering Advanced Merchandising Considering that 2012
Intelligence Node has made a tremendous impact in the eight years since company embarked on their journey to compile a wide product and pricing dataset.
Having a AI-powered algorithms, the company has mapped over 1 billion unique products across over 190, 000 brands along with 1, 400 product types. Users can access your real-time data in 29 languages with all the company’s InCompetitor dashboard.
Intelligence Node also serves users from an array of industries, including consumer gadgets, fashion and apparel, foodstuff and grocery, furniture and style, and beauty. Sanjeev instructed us the company’s dataset features helped generate retail profits of over $600 billion dollars worldwide.
“Intelligence Node is trusted by numerous retailers and brands worldwide, including industry leaders similar to Jockey, Unilever, Macy’s, Li & Fung, GFG, Tesco, Reliance, and Landmark, among people, ” he said. “Our competitive solutions allow these lenders to grow their full price businesses with data-backed, AI-led rates optimization. ”
Intelligence Node’s values include utilizing a growth mindset along with helping companies compete properly by adapting to appearing trends. Still, Sanjeev said it’s been an issue convincing retailers to transfer from intuition-based pricing to your more scientific approach in the past.
“Even today in your retail world, the tastes pricing and assortment decisions are produced using gut instinct not having much insight into the market industry, ” he said. “The average response time for it to a price change for Amazon is 60 seconds or so. The same blended average for ecommerce inside U. S. is approximately four weeks, whereas for the Oughout. S. brick-and-mortar sector, the blended average is around 270 days. ”
As outlined by Sanjeev, Amazon’s dynamic pricing has allowed the corporation to dominate the marketplace in recent times. “What we are looking to do is help retailers stay before curve by beating Amazon at a game, ” he explained.
Highly Accurate Data along with an Easy-to-Integrate API
Thinking ability Node delivers a sturdy product catalog — via software for benchmarking pertaining to pricing and assortment for you to price optimization and datasets furnished via APIs. But Sanjeev said your underlying value connecting each of the company’s services are substantial accuracy and instant plug-and-play gain access to.
“We provide highly exact and actionable data, ” they said. “Whether the retailer is small businesses or a giant similar to Walmart, our solution might be deployed instantly. We offer an API that could be completely integrated with your retailer’s tech stack within just minutes. ”
The company’s product repository API allows retailers to avoid wasting significant time and income on deployment and integration. To be sure consistency, the technology welcomes most product identifiers, which include barcodes, global trade object numbers (GTINs), and UPCs. The API returns normalized categories mapped as outlined by Intelligence Node’s proprietary procedure for data clustering and normalization.
In addition for you to easy setup, Sanjeev said the company’s high degrees of accuracy also serve as being a differentiator. “We host the largest plus the most accurate dataset out there, which has been crucial in providing significant savings for many of the world’s leading retailers, ” they said.
The platform in addition addresses standardization, a common pain point inside retail world. “To placed things into context, we track over 3, 800 variants in the color beige in your Asian lingerie market, ” Sanjeev explained. “What we offer to clients is the standardization on this data in their chosen format to ensure their teams don’t ought to learn new taxonomies along with ontologies. ”
When it relates to product development, Intelligence Node’s processes depend on adapting to the hottest trends and, of study course, listening to customer opinions.
“While we have a buyer success team that is actually updating product features determined by customer feedback manually, our solution is clearly driven by machine learning also, ” Sanjeev said. “With every single iteration, our solution adapts itself on the newest trends in the marketplace. This leads to dramatical growth, which is a core driver of our own extremely high accuracy. ”
Adapting to your Google-Driven Retail Environment
Intelligence Node recently added position in search results page (SERP) and field of vision data to its podium so users can take advantage of the full potential involving big data.
“Visibility is surely an extremely important factor that may be often ignored by stores, ” Sanjeev said. “Consumers are constantly seeking products on Google and also other search engines before setting up a purchase decision, whether on-line or offline. Hence, SERP insights can be a pivotal tool for good results in retail today. ”
Sanjeev said that retailers that not appear presents itself a page or inside top five listings can have difficulty generating sales. He added that firms with higher page rankings rarely should rely on discounts as well as promotions. A high ranking means the product is staying purchased for reasons aside from price, such as good quality, brand value, perception, as well as loyalty.
“A SERP-based product listing approach considers the product description, credit listing, and product impression score, among other components, ” he said. “It is a cutting-edge for retailers that have to get their products noticed along with purchased by customers — and will be central to most marketing efforts. ”.