This depends to an extent on what you define as your product.
One might argue that in our increasingly digitised world, the lines between product development and CRO (conversion rate optimisation) are becoming blurred.
For example, for a pureplay retailer like ASOS its website and the content it publishes are as much a part of its product as the clothes it sells.
The team behind the much-heralded GDS (Government Digital Services) project in the UK also blogged recently about how it has used analytics and testing to ‘provide feedback to GOV.UK to inform product development’.
The work done to tweak the UX could fall under both product development and CRO.
Are you still with me? Hopefully so.
And if you’re willing to accept the parallels between the two processes, then it appears most companies are addressing this issue.
Econsultancy’s Conversion Rate Optimization Report 2014 shows that after a year of relative stability in this area, companies are now more likely to have multiple people responsible for improving conversion rates.
There has been a 14% increase in the proportion of companies that have more than one person directly responsible for improving conversion rates, from 37% to 42%.
Do you have anyone in your organization who is directly responsible for improving conversion rates?
The use of analytics to inform product development is one topic that will be open for discussion at Econsultancy and IBM’s BusinessConnect 2015 events in March.
This series of interactive roundtables – hosted in Malaysia, Thailand and Singapore – allow you to join the dialogue with your peers and cross-industry experts to gather marketing insights on how organisations are transforming their respective businesses for the digital age with enterprise analytics.
Another take on this point is presented in an ebook published by IBM.
It argues that to facilitate a process of product development informed by data, businesses need to be implementing behavioural analytics.
This sophisticated set of analytics can provide insights into the decision processes of individual people making purchasing decisions.
According to IBM VP of strategy and product management Chris Wong, the company’s focus has commonly been on driving insights from transactional and performance-based analytics.
While these are considered descriptive analytics, understanding the current state provides a solid foundation for then predicting future outcomes.
However further analytics modelling is required to determine the cause of particular outcomes and issues so the relevant corrective action can be taken.
Models will then need to be refreshed as the market or product life cycle evolution changes to ensure that predictions and corrective actions continue to be effective.
To finish, here’s a quick case study that shows how IBM uses data analysis to adapt it digital strategy.
Its annual ‘Crunch Day’ event brings together employees from different teams to analyse data pulled from more than 400,000 tweets and develop recommendations based on the insights.
This yielded several useful recommendations. For example, it was discovered that a competitor was being more effective on key performance indicators that are important to IBM.
As a result the company took action, including a shift in marketing investment to ensure that the corporate message was more focused and effective in that channel.
To request for your exclusive invite to attend the Econsultancy/IBM BusinessConnect 2015 events, sign up here: