B2B organisations are increasingly understanding that data is a major asset that can provide great value to the business. But simply hoarding as much data as possible does not equate to value. Companies therefore must focus their efforts on gaining access to the information that will truly make a difference to their business performance.
Businesses typically use storage models that scale the costs according to usage, making vast data collection an expensive task. Most data stored in organisations will provide little value, either because there is no need to hold on to it or they lack the ability to use it. All too often, businesses just don’t know what data they have.
“Organisations need to undertake an investigative process to expose all the areas where they are currently hoarding data, whether they are using it or not, and why,” says Gareth Edwards, head of data science at Softwire, a software development firm. “Only once this exercise has been completed can any business really understand which data sets are of most value and which are being unnecessarily collected and stored.”
In most organisations, the grim reality is that information is all over the place. On average, 16 per cent of data is unknown, according to Veritas’s 2017 Data Genomics Index. The growth of unstructured data shows no signs of slowing, either, with a 50 per cent jump in the number of unknown files in organisations between 2016 and 2017.
It will ultimately be the role of people, ensuring the right questions are asked, that brings success
Digital transformation is ultimately defined by the value of information, so addressing this soaring volume of unknown files with appropriate data management tools is crucial in turning that data into genuinely useful insights for the business.
“This will allow businesses to deploy data classification tools that can scan and tag data in a granular, intelligent and automated manner to help them quickly discover, analyse and access it and on-demand,” says Jason Tooley, VP Northern Europe at Veritas.
Successful utilisation of data also relies on people. The managers in a B2B organisation know where the value comes from, and they know what answers they lack to create that value. But simply knowing what are the right questions to ask for data is not enough – they must communicate better with IT to develop systems that can find the answers.
Consumer brands are often perceived to be ahead of B2B companies when it comes to generating value from data, though this may be because their attempts to profile customers are more visible. B2B businesses selling devices, machines or tangible systems, in fact, generally have more valuable data -processing opportunities, particularly around areas like preventive maintenance and configuration optimisation.
The Internet of Things, which involves connecting objects with internet-enabled sensors that speak to each other, is also more prevalent in B2B scenarios and is one of the most powerful methods for collecting, processing and ultimately gaining value from data.
“What is complicated for B2B brands is when they produce a subsystem which is integrated in a larger system by their client – itself selling the larger system to the final customer,” says Yannick Meiller, assistant professor of information and operations management at ESCP Europe, the business school. “This is the case of Valeo in the car industry. The subsystem may be equipped with many sensors, but the data is captured by the main system, and therefore by the producer of this larger system.”
Accepting there is significant value in data is only the first step to realising its worth. B2B businesses must implement technologies and processes that ensure the correct data is collected and then integrated and analysed to find context. It will ultimately be the role of people, ensuring the right questions are asked, that brings success.
Companies in the B2C space have long understood the importance of effectively rewarding customers for their loyalty. But many B2B brands still believe that sending a Christmas hamper or bottle of champagne to long-term clients is enough to thank them for their long-term commitment.
While these types of gifts are not unwelcome, the advent of advanced data analytics, alongside several other innovative technologies, has made it possible for even small companies to better understand their clients and learn exactly what they want.
The future of rewarding loyalty will be underpinned by technological tools that empower staff to give customers exactly what they need, when they want it
Customers, too, are increasingly interested in being rewarded for showing loyalty. According to ‘The Loyalty Report 2018’, published by customer engagement agency Bond, a huge majority of people (87 per cent) say they are willing to have their activity tracked, if they get access to personalised rewards.
B2B brands can ensure their data collection is delivering value to their customers by using it to create a consistent omni-channel experience. Utilising data to engage customers on an emotional level can add value to the service offered to clients and, ultimately, make them more likely to remain loyal. Without detailed customer data it’s not possible to provide the most personalised rewards, insights, service and assistance during the entire customer journey.
A human element is still important to achieve a positive result for B2B loyalty programmes, but the future of rewarding loyalty will be underpinned by technological tools that empower staff to give customers exactly what they need, when they want it.
Accurately measuring B2B customer loyalty can be difficult as it’s hard to discern what activities are directly due to loyalty and which are, for example, related to competitive prices or offers. One of the most effective and obvious ways to calculate customer loyalty is the repeat customer rate (RCR). If a customer has been purchasing the same product every month for the past 10 years, this information can be used to access the success of new loyalty initiatives.
Using this rate is a solid baseline for quantifying loyalty but by joining the customer lifetime value (CLV) with RCR can give companies a deeper insight into the different segments of customers they are trying to reward. Clients that are both high-spenders and regular customers should be rewarded in different ways than low-value, regular customers, meaning the need to measure total spend and purchase frequency are highly important.
Perhaps the single most relevant metric to measure customer loyalty is the Net Promoter Score (NPS), which is the likelihood of the customer to recommend a company’s products or services to their colleagues. Unlike the B2C space, where individual needs are often the primary purchase consideration, B2B purchasers must factor in different purchase motivations around what the business itself needs.
So, it may be the case that a regular B2B purchaser is only buying products due to their low price and will move away the moment this factor changes. This type of consumer is hardly loyal and the NPS will uncover customers who are purchasing for other reasons than loyalty.
To be successful in the future of rewarding B2B customer loyalty will require each client to be targeted on an individual level and not as part of some larger grouping. It’s no small task to create an effective B2B loyalty programme, but with the cost of acquiring new customers being up to five times more expensive than increasing spend from current customers, it’s clear the investment will pay dividends over the long-term.
Australian-based steel producer BlueScope Steel first introduced its B2B-focussed loyalty scheme in a bid to increase the amount of money SME customers spend on its products. This programme, called ‘Constructor’, offers clients one point per dollar spent, which can then be used to buy items from a rewards catalogue, and provides customers with detailed information about the cost, special offers and opportunities to earn extra points.
B2B reward systems like this mark an important step in the journey to create an effective scheme that helps reduce customer churn and better engage with high-value clients. Yet, as BlueScope Steel soon realised, customer data was the key to making the most of the loyalty programme.
The company worked hard to ensure all data held on their customers was accurate and up-to-date, by improving how databases were managed, and established a fully joined-up system where customers received personalised offers based on their previous transactions.
By combining a reward system to incentivise B2B customers to become long-term clients with advanced data analytics that provides detailed information about customer intentions and expectation, businesses will be better placed to meet ever-changing client needs.
This data-driven approach resulted in bottom-line benefits for BlueScope Steel, with the firm reporting the 1,200 customers who are part of the ‘Constructor’ programme spend more than double they used to before the scheme started, leaving BlueScope Steel to concentrate on creating the best products for clients rather than focusing on managing margins.
Few people enjoy calling up a customer support line for advice to be greeted by an automated voice reading out an unpersonalised list of questions about why they are calling. But the next generation of natural language processing (NLP) software will allow customers to simply say or type their query and advanced chatbots can instantly analyse this input and offer a relevant reply.
The chatbots of tomorrow can move beyond answering specific questions like “Has my order left the warehouse?” to more complex questions that require detailed information about the exact circumstances of the customer, such as “What is the best printer for my business?”
2) Artificial intelligence (AI)
The role AI already plays in the B2B customer journey is significant, but there is far more this game-changing technology can achieve soon. Through using AI-backed solutions, businesses can make the customer journey more personalised and offer customers more accurate product recommendations based on recent purchases.
If research company Garner’s prediction, that, by 2020, customers will manage 85 per cent of their relationship with the enterprise without dealing with a human, proves correct, businesses who fail to incorporate AI tools into their customer experience journey will not keep up with consumer expectations.
3) Internet of Things (IoT)
With market research firm Statista forecasting that there will be close to 31 billion IoT devices worldwide by 2020, it’s clear the massive amounts of data collected by these tools can be used to gain valuable insight into the customer journey.
Machine manufacturers can include IoT-enabled sensors in their products to alert service personnel when the first signs of breakdown occur and send out repairmen to fix the issues before a major failure happens. In the future, these IoT devices will be able to communicate with each other and troubleshoot problems through AI, reducing the need for human interaction.
4) VR and AR
Virtual reality and augmented reality solutions are no longer futuristic concepts that have little practical application in the business environment. As VR and AR devices become more commonplace, how customers experience products will be fundamentally changed, especially in terms of how businesses can better listen to their customers’ needs.
Companies can share new product designs through VR and provide a detailed, visible guideline of the exact specifications and benefits their customers can expect. Using AR to see how potential products and blueprints fit into current operations allows customers to give more relevant feedback than ever before.
5) Data analytics
There’s little point in amassing large amounts of customer data if it isn’t going to be analysed to extract actionable insights. Cutting-edge algorithms can interrogate data to discern and predict what the customer wants at every point along their journey. From learning when to suggest certain products to tailoring prices to match customer expectations, mining data can provide a clear understanding of what clients need.
By using real-time data analytics, there will be no delay in discovering customer preferences and using this to personalise the services offered to them, improving companies’ ability to retain clients.
Powerful technologies like artificial intelligence (AI), augmented reality and chatbots may be enabling brands to enter a new phase of CRM, but a lack of thought into how these innovations actually come together to increase engagement risks isolating customers.
AI can ensure consumers receive personalised recommendations and targeted offers on their favourite devices and channels. Chatbots can give users a rapid response based on real-time consumer data. Augmented reality can bring products to life. When integrated and transparent, they allow brands to demonstrate that they value each customer.
However, when customer experience initiatives are run in isolation, human engagement is often lost. The best brands make experience their entire business and implement this ethos across every department – from marketing to sales, IT to customer services – so they can utilise insights from one another to drive better performance.
“By breaking down these organisational siloes, brands can gain a singular view of their customers across each and every touchpoint, and ensure they receive the most relevant, personalised experiences possible,” says Bridget Perry, VP of EMEA marketing at Adobe. “It’s the unified experience that’s key here – consumers feel they’re engaging with one brand and one brand only, giving their experience a more human feel.”
A connected user experience relies on personalisation, which can only be powered by customer data. In a world where media coverage of data breaches and new regulations like GDPR can inspire public scepticism in companies that collect data, organisations should clearly communicate the value customers will receive for providing information.
As well as enabling a personalised experience, predictive analytics can be a powerful tool for transforming that collection of data into more customer loyalty by highlighting bottlenecks and pinch points in the user journey. On a wider scale, it can highlight channel usage preferences and performance, allowing firms to prioritise resources.
First Direct, the online bank that commonly ranks highly for customer service in the UK, uses data to build a more complete picture of each user, meaning interactions can be personalised and issues resolved more quickly. However, Joe Gordon, who heads up the bank, says human interaction will always remain crucial to its customer experience.
“Processes will become increasingly automated and technologies such as AI will become more mainstream, but at the same time, what cannot be automated will become even more valuable,” says Mr Gordon. “People will always be needed and establishing emotional trust with your customers is what will really make the difference.”
It’s not just collection that can cause problems, but rather what organisations then choose to do with the data. According to research by global analytics firm SAS, 93% of businesses are unable to use data to accurately predict what individual customers will want. Many brands are trapping customers in a cycle of repeated recommendations.
There is no doubt that AI will play a significant role in improving the customer journey, but companies risk losing business by automating their communications using incomplete or irrelevant data. Even where the data is relevant, analysis tends to be retrospective, meaning firms often fail to establish the next best action for customers.
“Too many companies are not using all of the information available to make accurate predictions about their customers’ latest tastes and circumstances, trapping them in the digital shadows of their past selves,” says Tiffany Carpenter, head of customer intelligence at SAS UK & Ireland. “As a result, businesses are missing out on new revenue streams, not to mention the risk of damaging their customer relationships.”
Having a customer-centric approach when developing AI applications is essential. By limiting the efforts to incorporate AI and other innovation to only technical teams, businesses risk alienating users. For maximum value, the people who engage directly with customers need to work with IT to build a truly connected experience for users.
Marketers and researchers are still trying to determine how to create the right balance between human and non-human interaction across the customer journey. The challenge for businesses is they can try to design that journey, but customers usually decide how they use the touchpoints and often each user has a unique journey.
“In the short-term, I don’t see companies moving away completely from other forms of touchpoints, instead it will happen similarly to when telephone, social media and other new channels emerged,” says Dr Rodrigo Perez-Vega, a lecturer at Henley Business School. “Companies still give customers choices as to how they want to contact the firm, but in the long-term, human interaction might become part of a premium experience.”
As companies look to reap the benefits of automating elements of its CRM, it’s clear they must do so in a way that not only transparently documents their use of customer data and integrates technologies through departments and the business itself, but also doesn’t lose any human engagement. People will always want to buy from people.
Providing the best possible customer experience (CX) is crucial for any successful business. For this to happen, everyone in the organisation must be in sync with what’s going on in and around the company, particularly when it comes to customer interactions. That’s where Customer Experience Management (CXM) comes into play.
CXM expands and enhances the classic Customer Relationship Management (CRM) concept, which mainly operated as a contact management system. While it was a useful place to get telephone numbers, or to measure salespeople’s performances, it was never viewed as a crucial element in supporting the customer journey.
Thanks to CXM, that’s all started to change. Building on CRM, CXM solutions manage and intelligently act on the many layers of information flowing through a business along the various stages of the customer journey. CXM doesn’t just enable us to “market and sell”: more importantly, it helps us “develop and serve” our customers in a personalised manner. This can include interactions on social media, or personalising and optimising a customer’s favourite website. It can range from the development of fully servitised products using the Internet of Things, Case Management and Field Service Management to maximising product availability through predictive maintenance algorithms.
A modern CXM solution is a platform for all the communications within a company and covers touchpoints like the various digital channels that are now so central to business. CXM considers how happy customers are and whether they are likely to recommend your product or service to others, rather than simply looking to their next purchase or other company interaction. This deeper level of knowledge can provide unprecedented insights into consumer habits and the best ways to boost customer loyalty. It’s an integral part of digital transformation: rather than simply overseeing a spreadsheet of customers, it helps you seamlessly integrate the wide array of productivity tools that businesses now use.
CXM solutions manage and intelligently act on the many layers of information flowing through a business
Buying structures in businesses today are more complicated than ever. In retail, for example, there are multiple buying personas for every prospective customer, from professional (going to work in smart dress) to personal (walking the dog or going mountain biking). Each of these levels of information can be hugely valuable to a business that’s trying to take a new product to market or find people that might be interested in its service. CxM provides the platform to collate this information and – more importantly – the opportunity to add context and generate truly actionable insights.
When it comes to deploying a CXM solution, adopting the following approaches can bring immediate results.
- Think “outside in” and put the customer experience first. The ability to measure and articulate improvements in CX ensures that your efforts truly add customer value, and that you aren’t simply changing processes for the sake of it.
- Pursue a “unified” experience at all stages of the customer journey, including in the touchpoints where departments outside sales engage with and influence your customers. This should be a seamless and consistent experience, where the customer is seen as a single entity throughout. For example, marketing could use a modern Product Information Management (PIM) system to oversee brand and product campaigns, while operations could build field service frameworks or accelerate the introduction of servitisation models.
- Think “agile”, and don’t be afraid to experiment with proofs of concepts. Breaking the project into phases and building on the success of each will help deliver value into the business immediately and validate assumptions on potential return on investment. This also ensures the CXM system picks up users gradually as it moves through its various stages.
- Look to “digital feedback loops”. This Microsoft term describes the use of information to proactively establish and analyse relationships between customers, products and data. Remember, data is the lifeblood of any organisation. The intelligent business solutions of the future will focus less on chasing information and more on supporting decision-making through machine intelligence. It is essential to build this concept into any project.
By putting customers first and processing relevant information consistently to produce actionable insights, companies will gain a competitive advantage. Working with a partner like Columbus, with experience of the best solutions, technologies and approaches, will amplify your results. We work hard to understand our clients’ USPs. Our customers can leverage not only our experience of different products, but perhaps more importantly, our knowledge of what works in different industries to help deliver the best possible CXM solution. By conducting business process analysis, we can identify the surest paths to success.