The growing importance that e-tailers and e-commerce firms generally attach to data analytics can be seen in the shift within operations teams towards hiring more data scientists as well as the interest from senior management in gaining a better understanding of how customer engagement impacts revenues and sales.
The sheer volume of online traffic that retailers experienced during Black Friday is captured in vast pools of data but the question is: what insights and intelligence can it shed that can shape and drive future revenues?
It’s often said that information is power and this still holds true today, to a greater extent. In today’s digital economy, the power that information can wield lies in the insights that it can offer about customer and end user online behaviours and the impact on revenues and sales.
However, information without context is worthless and all too often the devil is in the detail if anything meaningful is to be learnt. Step forward the data scientist and the application of data analytics in all aspects of the organisation, from digital transformation to digital performance management.
1. Managing performance like a product – the need for speed and analytics
Today’s 24/7 always-connected digital marketplace puts the consumer firmly in the driving seat. Where once retailers could pay lip service to ‘customer service’, customer expectations and demands mean that retailers’ revenues and reputations are intrinsically linked to the performance of their digital estates.
Engineering and DevOps teams will need to manage performance like a product, by using data from monitoring solutions and advanced analytics to shift from firefighting the most recent issues or optimising the slowest pages to identifying the key areas that need attention.
This trend will make prioritisation of IT initiatives a key focus, and IT development, testing and optimisation for pages that create the most revenue will come to the forefront.
Business and IT groups will need to be more connected and collaborate more readily to facilitate the management of performance like a product, because revenue will depend on it.
2. Data analytics – the glue the binds digital transformation
Digital transformation, which has morphed from a corporate buzzword to really being a ‘thing’, will continue to gain traction in 2017. Data scientists will become the social ‘glue’ that will compel business and technology teams to work in close collaboration, because data teams will continue to discover strong correlations between business metrics and technical metrics.
Though many e-commerce companies will struggle to emulate leaders such as Amazon, by the end of 2017 a new data-driven culture will finally be mainstream. The role of BizOps will attain a higher profile, and business and IT pros should lay the groundwork to start collaborating if they haven’t already done so.
3. Machine learning will evolve beyond theory into a business reality
Machine learning (ML) will move out of the lab and into the real world in 2017. Faster and more targeted responses to systems issues will take place, because ML models will be trained and installed in production systems, predicting outcomes and detecting abnormal events and system states, enabling IT teams to get out ahead of problems.
What’s more, ML means that problem alerts will carry context created through big data insights that support quick diagnosis and remediation. Artificial intelligence paired with ML will become key, because there is simply too much data and too little time to manually drill down into all of it; ML will add valuable and time-saving context.
In addition, advanced alerting and web integration (webhooks) will tie all of these forces together to ‘machine assist’ diagnostic and remediation activity and thus become central to performance management that drives revenue.
4. Emerging new capabilities will drive actionable insights
New technologies, including stream processing and data integration in the stream, will emerge. Near real-time data integration using data APIs and solutions like Big Beacon and BlockChain will become more common and offer a preview of powerful future capabilities.
Traditional ETL (extract, transform and load) and data warehouses are cumbersome and will go by the wayside due to friction and entropy. An incredible amount of data exists in the enterprise, but actionable insights are still thin on the ground. Stream processing and data integration will expedite the gathering and delivery of data insights and data analytics overall.
5. Data analytics – a constant in a sea of change
2017 will continue to be a year of constant change, but data analytics will serve as a beacon for organisations sailing into uncharted waters. The data may never lie, yet making sense of the sheer volume of data is the challenge facing e-tailers and e-commerce firms.
Digital performance management will be critical for e-tailers and e-commerce firms that need to provide the best customer experience possible to drive revenue. In a hyper-competitive economy, under-performing systems, applications and even web pages – the culprits that leave money on the table due to lack of conversions – will be more easily identified, helping enterprises and IT teams prepare for high-traffic events like Black Friday, as well as other high-traffic, and even chaotic, situations.
Data analytics will continue to increase in value to enterprises and e-commerce companies, thanks to the meaningful insights that they reveal about consumer shopping habits, preferences and behaviours.
This is especially important in an era where consumers’ online expectations and behaviours are measured in milliseconds, while digital transformation impacts more companies and sectors of the economy, and as machine learning goes mainstream, along with new, emerging methods of processing data.
Combine all of these factors, and you set the stage where data analytics and performance management are an integral part in driving and shaping online revenues.
Sourced from Vincent DeGennaro, GM, EMEA, SOASTA