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The Hub Of Data Science Innovation
<p>NeenOpal is a global big data consulting firm with a unique and specialized focus on Data Science, Business Intelligence, and Customer Relationship Management solutions. We aim to drive Digital Transformation for our customers, ranging from budding startups to large corporations, leveraging their data for disruptive and exponential growth. Our highly competent and industry-experienced workforce ensures we deliver state-of-the-art solutions at a competitive price while accelerating the time to market of our customers\' strategic initiatives. </p>
$25 - $49/hr
10 - 49
United States
NeenOpal is a global big data consulting firm with a unique and specialized focus on Data Science, Business Intelligence, and Customer Relationship Management solutions. We aim to drive Digital Transformation for our customers, ranging from budding startups to large corporations, leveraging their data for disruptive and exponential growth. Our highly competent and industry-experienced workforce ensures we deliver state-of-the-art solutions at a competitive price while accelerating the time to market of our customers' strategic initiatives.
1460 Broadway C/O WeWork NYC New York United States 10036
6467930813
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Marketing mix modelling is statistical technique to determine decision making via evaluating effectiveness of marketing initiatives and thereby increasing ROI.It can be hence a key factor impacting success or failure of a product. By knowing details of impact of each marketing activity on sales it is easy to allocate resources to activities who will maximize the revenues & cut spending on activities who are not generating enough revenue Improve ROI on existing investments Understand which campaigns you are overspending / underspending Efficienly allocate marketing budgets A simulator was built in Power BI using which the Markteing Team could see the impact of sales by changing the spend on various marketing mediums. You can read more details here - https://www.neenopal.com/Marketing-Mix-Modeling.html
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