With the rise of Big Data, organisations are able to see how their customers really perceive them. B2C organisations are utilising Big Data when it comes to customer experience, however, B2B organisations are still facing challenges when it comes to understanding the customer experience.
Manufacturers can use the new approaches to data analytics which have been described by Dr Mohamed Zaki and Dr Benjamin Lucas from the Cambridge Service, to help them transform their customer experience and have a competitive advantage.
Organisations have relied on Net Promoter Scores (NPS) and satisfaction surveys which are more traditional methods used to measure and quantify the loyalty of an organisation's customer relationships. These methods often fail to provide a true insight into the customer experience, meaning that organisations are lulled into a false sense of security, by which point is often too late to notice unsatisfied customers.
Customer experience analytics allow managers to gain a much richer understanding of their customers and their interactions with the organisation throughout the whole process of the 'customer journey'.
An article in Forbes states that "53% of companies are adopting Big Data Analytics, with telecom and financial services industries fuelling the fastest adoption".
"The first change we had to make was just to make our data of higher quality. We have a lot of data, and sometimes we just weren't using that data and we weren't paying as much attention to its quality as we now need to" from Ash Gupta, Chief Risk Officer at American Express on big data and data analytics.
1. The jump to B2B
A McKinsey report in 2016 highlighted the fact that B2B customer-experience index ratings are considerably lagging behind those of retail customers despite the B2B customer expectations increasing fast.
The value of customers and customer loyalty within B2B organisations is paramount and so is increasingly important that customers do not become unimpressed with a lack of service innovation in the workplace.
Within B2B purchasing, multiple stakeholders are usually involved in the decision-making process and so organisations face a challenge satisfying their customers.
In order to understand their customer’s experience, sophisticated analytical tools are required.
2. Big Data
The value chain which has become increasingly digitalised allows organisations to have large amounts of data at their disposal.
Large amounts of data are useful, but only if it is analysed in an accurate and meaningful way.
We need to know what questions to ask and how to ask them to make the most out of the data available.
Customer surveys tend to use scale questions which allows organisations to create metrics such as NPS, as well as text fields to allow respondents to input their own comments.
Graph visualisations can be used to show the customer feedback, with individual responses coloured by the NPS categories.
The metrics that are used based on customer surveys do not provide the organisation with an accurate image of the customer experience, whereas the individual comments that respondents make can be used to make detailed decisions.
3. Focus on customer experience
Customer Experience allows for a much deeper understanding of customer decisions at each stage of the 'customer journey'.
The cognitive, emotional, behavioural and social dimensions of customer behaviour are utilised and incorporated into a framework for the customer data which allow a more functional measurement of how well a service or product is performing.
When these dimensions have been defined, they are incorporated into the data set and machine learning will allow the scoring of customers on only aspects that matter to them, therefore are more tailored to the individual customer.
This data allows organisations to pinpoint any critical data that highlights any underlying issues along the 'customer journey' and provide insight as to how and where an organisation needs to make changes in order to improve their customer satisfaction and experience.
Greater connectivity comes with greater expectations
It is becoming increasingly important that manufacturers learn how to understand, manage and measure customer experience. These new analytical approaches give manufacturers the opportunity to lock in their loyal customers with richer, more accessible, more bespoke and more responsive services.
The challenge comes from not creating and providing a service that your customers require. See below for additional posts relating to manufacturers and how they can gain a competitive advantage:
There’s no lack of a sense of urgency. Faced with workforces that are anxious about health and safety, their job security and even the viability of your current way of doing business, senior leadership needs to quickly find a way forward. How can you swiftly capture that imperative to do things differently, and mould it into robust new processes and tech that won’t put you at even greater risk?
Data is essential for measuring business success, but if you haven’t moved your analytics to the cloud, you could be missing out on a goldmine of hidden insights that modern tools will help you unlock. Let’s discuss those tools and their benefits…
Collecting customer data and generating reports is one thing, but are you sure you’re using it effectively? Here are a few metrics worth keeping an eye out for when obtaining that data, as well as our top tips for maximising your data.
Choosing a product information management (PIM) system can be overwhelming. You’re aware of the benefits a PIM will provide for your business, but where do you begin looking for the best one to support your business?
In today’s business world, data and analytics are transforming nearly every industry and fresh food produce is no exception. In this blog, we’ll examine four areas where advancements in technology, data and analytics are changing the way produce companies operate and the benefits they get as a result.