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Sapient’s Prashant Mehta on how data can help in cutting costs

With evolving and accessible technologies, the benefit of data has now been leveraged by almost all retailers, therefore the competition now lies in the visualisation of the insight the data provides and translating it to solutions. Prashant Mehta, VP & Global Service Line Lead – Systems Integration & Data, SapientNitro offers insights on how big data may change the statistics of profit for many.

Integration of data to obtain a comprehensive source pool
The goal of marketing automation is to predict the consumer’s next mood and moves, not only a specific moment’s reaction. To achieve that there is a need to have very comprehensive, detailed understanding of the patterns that data presents.

According to a survey by Netsertive and the CMO Council, 42 per cent of marketers admit they face a lack in data insight that may be used to drive consumers into physical retail stores. While 23 per cent are using third-party tools like Google Store Visits or FourSquare Attribution, it is suggestive that the full potential of data input is not being leveraged as only three per cent track e-receipts, six per cent track in-store redemption of promotional offers delivered via digital channels, and 10 per cent track digital coupon redemption. That essentially, is against the sense of the ‘omnichannel’ approach, as ‘omnichannel’ is more about listening than projecting.

“There is also a great opportunity to leverage conversational Interface, driven by machine learning, such as Alexa, to drive a more natural way of engaging consumers leading to higher conversion and impulse buying.  With the 360° Customer View, an organisation can provide consistent service to a customer across all departments, from marketing to sales, operations, finance, and other business functions,” said Mr Mehta.

While brands can use this as an opportunity to capture data as a means to provide a personalised consumer experience with relevant information to address their needs, this is challenging as well, he feels, as it requires brands to develop a seamless customer journey across disparate channels. “However, with the power of data analytics, brands can solve this problem by collecting information and stitching a unified customer journey at scale and in a real time manner,” he added.

Conjuring a story with the data obtained
Thanks to solutions like Amazon Mechanical Turk, collecting data from around the world has become a much easier job. However, the challenge lies in evaluating the data.

“Raw data is complex to process with levels of structured, semi-structured and unstructured data. This needs to be cleaned, filtered for noise, and converted into a format that can be easily used to draw insights,” said Mr Mehta. Indeed, data can become a roadblock, if not visualised to the right effect.

As Mr Mehta acquiesces, modern data technologies like Hadoop and Spark make it possible to filter out the noise effectively and analyse large volumes of data from various sources. Many companies have come up with innovative solutions for end user data preparation for big data such as Alteryx, Trifacta, Paxata and Lavastorm and Informatica. With the advent of user-friendly tools even people without extensive data knowledge may be able to sort the information to produce values.

“However, while the data acquired may be sorted into clusters, patterns and associations using various techniques like statistical modeling or machine learning, the key to telling a story is how one is visualising the insights. With modern data visualisation tools, there is resort to interesting representations of insights rather than standard pie charts and bar charts along with an option to create custom solutions with technologies like JavaScript to provide intuitive visualisation,” he said.

How the data story may help cost optimisation
Churn prediction has been one of the approaches by SapientNitro: where they majorly tried to predict the churn of a customer by analysing their behaviour on various touch points. Such a strategy may greatly serve to ensure greater ROI on marketing spends, by enabling better segmented content to reach different groups.

For ecommerce companies, an analysis of transaction attributes and customer profiles may help to regulate process improvement. “Reverse logistics pose a great challenge to retailers, which can be avoided by predictive analytics. Retailers have all historic information of purchases made. By envisaging the potentials through comparison of attributes/customers, they can predict the likelihood of a return/rejection. COD transactions are as large as 50 per cent of the total orders whereas, return of products amount to 20 per cent,” stressed Mr Mehta.

According to him, logistics optimisation- which includes supply chain optimisation or delivery route optimisation is a major clause in process improvement. “This is possible by predicting the future orders by analysing the past and proactively shipping the goods to fulfilment centers or warehouses. Delivery route optimisation is a major improvement since 50 per cent of the total cost is involved in the last mile delivery,” he added.

With Internet of Things amplifying multi-directionally, a petabyte-scale data explosion is destined. The size of IoT machine-to-machine data is likely to exceed in-memory capacity by orders of magnitude. Therefore Data lake technologies are promising to be beneficial in terms of cost and storage with Google, Amazon Web Services and Microsoft developing services where the data can be collected and directed to cloud based analytics engines.

It is a bright prospect, felt Mr Mehta, as companies can leverage a Customer Data Platform to ingest data across multiple first party data (CRM, commerce / Transaction data, loyalty, etc.), second party data (from partners) and third party data (DMPs) to create a DataLake which can form the basis of a 360 view of the customer. “These can prove helpful in driving one-to-one marketing or personalisation for an enhanced customer experience which can help in reducing the campaign / promotion costs while increasing the impact,” he said.

While big data technology is evolving at a rapid pace, is it a challenge to keep the workforce abreast with state of the art technology? “At SapientNitro, in addition to technology training, we also invest a lot in ramping up people on industries (FS, Travel, Retail, CPG,etc.) as well as domains / solutions (Media, campaign, content, etc.) that are needed to drive deep understanding of the business problem that we are ultimately solving for. We also look for people from the industry with strong experience in specific areas. This is required since they bring a different perspective and can help the team become even better,” concluded Mr Mehta.

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