iQuanti ALPS Tool Delivers Over 70% Accuracy in Predicting Google Search Results

Tool uses proprietary data science and machine learning to build SEO roadmap

News provided by

Nov 13, 2018, 09:06 ET

JERSEY CITY, N.J., Nov. 13, 2018 /PRNewswire/ -- iQuanti, a data-driven digital marketing firm, today announced that its predictive SEO tool, Analytics Led Platform for Search (ALPS), now delivers a 70%-75% correlation to the top 10 results in Google searches. The ALPS platform is built for enterprise-level execution, providing data-driven insights into how search can lift a brand's overall acquisition efforts by aligning and optimizing its organic strategies.

ALPS allows users to view key SEO drivers in a clear dashboard, including content, authority, technical and social analytics, while also providing users the ability to benchmark competitors' performance against their own. The tool allows users to see the likely impact of changes to their SEO strategy by predicting the organic rank for a URL before it goes live and analyzing how the new/optimized content positively or negatively impacts existing keywords.

While most analytics tools focus on traffic at a page level, ALPS goes beyond that to account for how each keyword contributes to the overall page value, allowing the user to optimize the most important and effective keywords based on likely impact.

ALPS includes a number of custom-developed algorithms to identify relevant keywords and estimate the impact each keyword has on traffic, including:

ALPS' Ranking Algorithm: The algorithm uses deep learning and advanced data science to do a holistic analysis of the contributions of 100+ enterprise SEO drivers across content relevance, authority, technical accessibility and social popularity to understand their individual and collective impact on organic search ranks.
ALPS' Simulation Capabilities (patent pending): The algorithm predicts simulated changes to a page's SEO performance by considering variations in content or backlink profile while keeping other parameters constant. The performance change is predicted in terms of rank, traffic, conversions and revenue.
ALPS' Relevance Algorithm: The ALPS relevance algorithm considers both semantic similarity between texts and the weighted density of a piece of text occurring in a larger body of page copy. Relevance is calculated between a URL's content and its target keywords, and between the content of backlinks to a URL and the URL's content.
ALPS' Traffic Estimation Algorithm: ALPS' proprietary CTR algorithm controls for various elements in the SERP layout (number of ads on page, presence of rich snippets, local packs, etc.) to greatly improve the quality of SEO analysis. The algorithm does predictive analysis of how each keyword contributes to the overall page traffic, allowing attribution of page conversions/sales to keywords.

Together, these algorithms create a predictive roadmap for enterprise brands to achieve a particular rank for a group of keywords – while also highlighting the expected difficulty of reaching that rank. In addition, by forecasting traffic, conversions, and revenue for a target rank position, ALPS offers insight into the search channel's true business impact.

"The overall aim of ALPS is to help brands build a solid SEO business case and create a roadmap for delivering it," said Viswanatha Rachakonda, CEO, iQuanti. "ALPS is intended to help users stand out in an increasingly competitive environment as well as efficiently develop new content and tools that drive customer engagement."

About iQuanti
iQuanti is a data-driven digital marketing firm that uses analytics and proprietary models to deliver high-performance marketing programs. With more than 10 years of experience, iQuanti turns consumer insights into actionable growth strategies for some of the nation's largest companies. iQuanti's proprietary ALPS tool leverages predictive modeling and algorithmic simulations to drive more effective client campaigns.

CONTACT:
Bill Daddi
Daddi Brand Communications
646-370-1341
917-620-3717
[email protected]

SOURCE iQuanti