How is Pulse calculated?

Pulse, Centricity’s proprietary metric, measures consumer interest in particular categories, subcategories, products, and Facets. To generate Pulse scores, Centricity ingests 2.5 billion online consumer interactions per day, ranking products on raw web traffic based on the likelihood a page viewer is to purchase certain items. Simply put, Pulse puts a number to what your customers want, how much they want it, and where they're looking for it. 

Centricity focuses on wide-ranging, forward-looking interactions — in other words, we don’t depend on Amazon best-seller lists or social sites. We believe that true consumer intent is measured through the actions that precede purchases, long before those purchases are actually made. In this way, we give you actionable consumer insights before there’s a signal in the market. And, because your organization’s sales data can be integrated into our platform, you’ll see where products are lagging, meeting, or exceeding real-time demand.

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Total Pulse is calculated as follows:
Total Pulse = (Page Views) * (Entity Pulse)

Step One: On a given URL, a single product may be mentioned several times. We refer to each mention as an Instance.

 

Step Two: Each Instance is assigned a Pulse score, from -5 to 5.

Step Three: A product’s overall Pulse score for a given URL is calculated by averaging the Pulse scores for all Instances on that page. We call this grouping a Product Entity, meaning several Instances referring to the same product.

Step Four: In this example, Entity Pulse is the average of the three unique Instance Pulse scores, calculated as follows: 

Entity Pulse = (sum of all Instance Pulse scores) / (number of Instances on URL)

Entity Pulse = (-2 + 3 + 3) / 3
Entity Pulse = 4/3, rounded to the nearest integer = +1

Step Five: Total Pulse is then calculated using the formula below. Assume this URL has been viewed 100k times in the last month.

Total Pulse = (Page Views) * (Entity Pulse)

Total Pulse = 100k * (+1)

Total Pulse = +100,000

 

Centricity aggregates the Pulse scores from all URLs we ingest, then we rank the products and filter the data by geolocation, accurate to within a 1km radius anywhere in the world, as shown below. 

We tag each product with specific attributes, or Facets, unlocking higher levels of granularity and novel analysis. Below is a portion of the Facet list we use to analyze products within the Toys category:


 

 

More questions about Centricity? Check out our website or talk to our Support Team.