New product engagement analytics - Input Data points to analyze

What are some of the input data points which can be leveraged to analyze the degree of engagement consumers have with the new product ?

Anonymous users engagement data

1. Date of event
2. Product engaged with
3. Event type ( Price checked, Feature configured, gif enlarged etc )
   

Registered user engagement data

• User id
• Age
• Sex
• Profession
• Product engaged with
• Event type ( Clicked to enlarge, Price checked, Feature configured like color etc )
  
  

Blog / User comments structure

• Product blogged
• Website blogged
• Date blogged
• # of blogs about the product
• # of positive sentiments
• # of negative sentiments
• Top 3 key words to express positive sentiment
• Top 3 keyword to express negative sentiment
  

Competitive blog intelligence

• Competitive Product blogged
• Website blogged
• Date blogged
• # of blogs about the competitive product
• # of positive sentiments
• # of negative sentiments
• Top 3 key words to express positive sentiment & their frequency
• Top 3 keyword to express negative sentiment & their frequency

Retail New product engagement analytics scenario ( NPD )

There are 5 levels of engagement a customer can have in the virtual world
1) When he clicks on a product which shows a degree of interest in the product
2) When he enlarges the photo of the product to see how the product looks in a magnified form shows even greater interest on the consumer
3) When he checks the detailed features page to see all specifications of the product it shows slightly greater interest
4) When he actually checks the price page it implies there is some level of purchase consideration
5) When he actually emails the page to a friend it is the highest form of engagement the consumer is having with the product as he is referring it to a friend




What are some of the business questions which can be answered from the above

1) Which are the top 3 products which are engaging the customer?
2) Which are the products which find least engagement with the customer?
3) Which products are being emailed most frequently and how many of them have touched the price page?
4) Which configuration features for Titanium ring are being configured most often ?

4 key points about New Product Launch analytics

- NPD using analytics involving blogs, product engagement event data involves people into the design process which is more realistic than just survey based data

- NPD can save CPG companies a lot of money since it can filter out products which do not show ‘resonance’ with customer sentiments upfront.'

- The interaction with consumers that NPD analytics leverages and essentially mining their “attention” using behavioral models is invaluable to integrating their opinions into product and service development.

- NPD Analytics using blog/sentiment and gaming configuration data distinguishes leaders from laggards – playing a pivotal role in deciding which products to take to launch stage, which attributes of products are finding deeper engagement, optimizing market message by mining the engagement data from consumers

Customer analytics and New product launches

There are about 150,000+ new CPG products launched globally every year.
Less than 10 % of new product launches achieve success. These 2 statistics are very telling about the amount of money being spent

With every launch organizations spend millions in dollars in researching new products, test marketing it and releasing it to the broader market. If the new product launch succeeds, it will result in significant enhancement to their revenue stream. If it fails it could result in millions of dollars going down the drain. It is a high risk, high returns game.

In these troubled economic times, organizations may want to be more cautious with their new launch initiatives as if the product 'bombs' in the market it could have disastrous financial consequences. The traditional process of assessing new launch product consists of analyzing a limited set of data like new product market survey data may need to be enhanced by understanding consumer engagement at a deeper level

Increasingly organizations are increasing the breadth of data analyzed to give a more holistic understanding of consumer acceptance of products which include the following additional inputs to the data

- Mimic a small virtual game for new product and observe people exploring the product
- Sentiment analysis of consumer feedback from blogs and social network sites


Traditionally these additional inputs were not accessed, but as many organizations are finding out, they may be better indicators of which products to bet on than traditional market survey data which is sample based and error prone.. CPG companies must reduce the high failure rate of new products; unearthing what “most people want. Today’s high niche market requires companies to add new tools to their research methodology that enable them to connect with thought-leading consumers and fully understand their demographic mix

The web provides an immersive environment for consumers to play around with new products which are launched