Business
HAS COVID CONVERTED CUSTOMERS TO CONVERSATIONAL AI?
Published
3 years agoon
By
admin
By Cathal McGloin, CEO of ServisBOT
A recent webinar hosted by Insurance Post asked customer service experts working at leading insurance companies whether social distancing would cause the demise of the traditional contact centre.
It was noted that, at the start of lockdown, insurers had anything between 15% and 50% of their contact centre employees working from home, which created a particular challenge for offshore operations. The assembled experts discussed whether they had seen any impact on customer satisfaction levels as their customer service colleagues adjusted to working from home.
Shorter queues
Andrew Jones, Head of Express and Retail Claims at Zurich insurance, noted customers’ willingness to use online portals because they assumed they would be waiting in a queue if they called the contact centre.
David Thompson, Director of Claims at Tesco Underwriting, noted that at the start of the UK’s lockdown in March, customers showed a great deal of empathy for the difficulties facing insurance contact centre staff as they adjusted to working from home. However, he noted that this early goodwill appeared to be returning to pre-COVID levels towards the end of September.
The webinar participants were asked to what extent technology such as chatbots and digital AI assistants had been used to assist with triaging insurance claims, to alleviate some of the pressure on contact centre staff, while still looking after customers.
David Thompson, Director of Claims at Tesco Underwriting, emphasised that when customers have been involved in traumatic events, they need to speak to a contact centre agent and value the empathy that can be provided during these conversations, adding “but certainly, there will be others who will be happier going through a digital journey.”
Paul Ridge, Banking and Insurance Specialist at SAS UK & Ireland, observed that consumers are becoming more accustomed to a range of channels available to them and a number of insurers are exploring how this shift could be used to introduce lower cost channels.
Distance Drives Digitisation
Ridge noted the value of using automation to take simple, routine, lower value tasks away from contact centre staff, so that they can focus on those customers who need more support. He believes that a good blend of technology and human skills can be used to benefit both employee experience and customer experience.
David Thompson agreed that automation and digitalisation had been ‘turbo-charged’ by the national lockdown. He underlined the importance of using technology to support the wellbeing of contact centre staff, noting that employee experience feeds directly into customer experience.
As Deloitte’s MD of Applied AI practice, Sherry Comes has observed, “While robotic process automation (RPA) and one-touch ordering buttons are transforming many of these tasks, they don’t always provide the most customer or worker-centric experience. However, finely-tuned conversational systems can.”
By employing conversational AI to understand the customer’s intent and automate the tasks and responses involved in issue resolution, or escalate their query to the right contact centre agent, resolution and CSAT levels remain high, while also reducing the number of routine issues that agents handle.
Digital AI assistants are key to driving down the cost to serve through either fully or partially automating routine customer interactions. AI assistants can also use these interactions to prioritise the correct course of action if they cannot fully automate to completion. By gathering pertinent information that can be passed on to agents, digital AI assistants save customers from having to repeat themselves once they get through to a customer service agent, helping the agent to resolve the issue more swiftly.
The personal touch
Conversational AI applies natural language processing so that customer intent can be understood, appropriate responses can be provided, and actions can be automated to solve their issues, while still providing the option to speak to a human. The advantage is that consistent, high-quality responses can be provided at scale, without overwhelming contact centre employees when human resources are stretched because some employees are self-isolating, or when the organisation is handling a sudden spike in customer enquiries.
While enabling financial organisations to automate repetitive transactions, conversational AI also allows them to be personalised by referring back to elements of previous interactions. The benefit for customers is that they don’t have to repeat themselves and conversations can be picked up where they left off, at the customers’ convenience.
Designed for Digital Natives
According to Deloitte, “younger generations seem to be gravitating toward accessing information through chatbots, with 70 percent of millennials reporting a positive experience after using them.”
Whatever their age, when applying conversational AI, brands must make it clear to customers that they are engaging with a digital assistant and not a human. It’s equally important to avoid trapping customers in a ‘bot loop’ and to provide a clear route to speak to a human if a query can’t be resolved by the digital assistant.
PWC believes that organisations that get their branding and persona development right within their conversational AI can create a customer experience that is akin to engaging with a human agent. However, getting it wrong will alienate users. EY emphasises the need to use the right data when ‘training’ conversational AI, explaining that “The bot uses logic to determine user inquiries and connect with enterprise systems to get the desired results”. Therefore, the bot is only as smart as the data used to build it.
This is why The AA Ireland invested time in studying genuine livechat conversations when developing its successful chatbot project, the Quote Helper Bot, so that they understood what people asked, how they asked, and what the intent was behind their questions. As a result, the Quote Helper Bot provided consistent on-brand responses that were based on live chat conversations with previous customers who had the same requirements. When social distancing measures were introduced in March, The AA Ireland was able to re-apply what it had learned and quickly spin up a call deflection bot, within 48 hours, to ease pressure on contact centre staff as they adjusted to working from home.
The future:
Paul Ridge observed, “The pandemic has given us the chance to glimpse into the future and see what role the contact centre will serve.”
Andrew Jones, Head of Express & Retail Claims, Zurich, commented, “A lot of claims are settled without using voice. In the future, rather than big contact centres, we’ll see more smaller collaboration centres, with people coming in one or two days a week and for training”.
Angus Rogers believes that the traditional service model will change, saying, “There will always be a need for people to work together, but I think that the model of the contact centre we see today will change.”
What we have seen is that organisations are using a blend of conversational AI and highly skilled customer service agents to automate routine enquiries, swiftly adapt working practices to abide by social distancing rules and deliver the right experience for customers and employees alike.”
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Business
Unlocking the Power of Data: Revolutionising Business Success in the Financial Services Sector
Published
17 hours agoon
June 8, 2023By
admin
Suki Dhuphar, Head of EMEA, Tamr
The financial services (FS) sector operates within an immensely data-abundant landscape. But it’s well-known that many organisations in the sector struggle to make data-driven decisions because they lack access to the right data to make decisions at the right time.
As the sector strives for a data-driven approach, companies focus on democratising data, granting non-technical users the ability to work with and leverage data for informed decision-making. However, dirty data, riddled with errors and inconsistencies, can lead to flawed analytics and decision-making. Siloed data across departments like Marketing, Sales, Operations, or R&D exacerbates this issue. Breaking down these barriers is essential for effective data democratisation and achieving accurate insights for decision-making.
An antidote to dirty, disconnected data
Overcoming the challenges presented by dirty, disconnected data is not a new problem. But, there are new solutions – such as shifting strategies to focus on data products – which are proven to deliver great results. But, what is a data product?
Data products are high-quality, accessible datasets that organisations use to solve business challenges. Data products are comprehensive, clean, and continuously updated. They make data tangible to serve specific purposes defined by consumers and provide value because they are easy to find and use. For example, an investment firm can benefit from data products to gain insights into market trends and attract more capital. These offer a scalable solution for connecting alternative data sources, providing accurate and continuously updated views of portfolio companies. Using machine learning (ML) based technology enables the data product to adapt to new data sources, giving a firm’s partners confidence in their investment decisions.

Suki Dhuphar
But, before companies can reap the benefits of data products, the development of a robust data product strategy is a must.
Where to begin?
Prior to embarking on a data product strategy, it is imperative to establish clear-cut objectives that align with your organisation’s overarching business goals. Taking an incremental approach enables you to make a real impact against a specific objective – such as streamlining operations to enhance cost efficiency or reshaping business portfolios to drive growth – by starting with a more manageable goal and then building upon it as the use case is proved. For companies that find themselves uncertain about where to begin their move to data products, tackling your customer data is a good place to start for some quick wins to increase the success of the customer experience programmes.
Getting a good grasp on data
Once an objective is in place, it’s time for an organisation to assess its capabilities for executing the data product strategy. To do this, you need to dig into the nitty-gritty details like where the data is, how accurate and complete it is, how often it gets updated, and how well it’s integrated across different departments. This will give a solid grasp of the actual quality of the data and help allocate resources more efficiently. At this stage, you should also think about which stakeholders from across the business from leadership to IT will need to be involved in the process and how.
Once that’s covered, you can start putting together a skilled team and assigning responsibilities to kick-off the creation and management of a comprehensive data platform that spans all relevant departments. This process also helps spot any gaps early on, so you can focus on targeted initiatives.
Identifying the problem you will solve
Now let’s move on to the next step in our data product strategy. Here we need to identify a specific problem or challenge that is commonly faced in your organisation. It’s likely that leaders in different departments, like R&D or procurement, encounter obstacles that hinder their objectives that could be overcome with better insight and information. By defining a clear use case, you will build a real solution to a challenge they are facing rather than a data product for the sake of having data. This will be an impactful case study for your entire organisation to understand the potential benefits of data products and increase appetite for future projects.
Getting buy-in from the business
Once you have identified the problem you want to solve, you need to secure the funding, support, and resources to move the project ahead. To do that, you must present a practical roadmap that shows how you will quickly deliver value. You should also showcase how to improve it over time once the initial use case is proven.
The plan should map how you will measure success effectively with specific indicators (such as KPIs) that are closely tied to business goals. These indicators will give you a benchmark of what success looks like so you can clearly show when you’ve delivered it.
Getting the most out of your data product
Once you’ve got the green light – and the funds – it’s time to put your plan into action by creating a basic version of your data product, also known as a minimum viable data product (MVDP). By starting small and gradually enhancing with each new release you are putting yourself in the best stead to encourage adoption and also (coming back to our iterative approach) help you secure more resources and funding down the line.
To make the most of your data product, it’s essential to tap into the knowledge and experience of business partners as they know how to make the most of the data product and integrate it into existing workflows. Additionally, collecting feedback and using it to improve future releases will bring even more value to end users in the business and, in turn, your customers.
Unlocking the power of data (products)
It’s crucial for companies in FS to make the most of the huge amount of data they have at their disposal. It simply doesn’t make sense to leave this data tapped and not use it to solve real challenges for end users in the business and, in turn, improve the customer experience! By adopting effective strategies for data products, FS organisations can start to maximise the incredible value of their data.
Business
Making the Maths Work: Addressing Inflation Challenges through Measuring and Managing Risk
Published
1 day agoon
June 8, 2023By
admin
Matt Clementson, Head of Enterprise UK&I
Persistent inflation is highly troublesome for every business – with or without a recession. In addition to causing unexpected expenses, it complicates decision-making around stabilising wages, setting product prices, and investing in new areas for growth. Meanwhile, stock and bond prices plummet when alarming inflation data arrives and interest rates increase. It’s time to run leaner, making the reassessment of the strategic objectives highly urgent.
With a seat in the boardroom, CFOs can guide thoughtful discussions covering everything from procurement, resource allocation, and manufacturing to the alignment of business purpose with operational tactics and goals. CFOs must also rethink how their business measure and mitigate risk. Understanding the business’ vulnerability, they can add considerable value to their business by identifying risks early and making organisations accountable for mitigating them.
When the economy becomes uncomfortable, the mathematics behind business operations no longer work seamlessly. During more comfortable times businesses have the luxury to accept some degree of inefficiency and low productivity – but in times like these that’s no longer the case.
So now it’s more important that ever for CFOs to use the right tools and technology to manage and mitigate risk and build business resilience.
Enhancing visibility to measure and manage risk:
To navigate through periods of high inflation, CFOs need technologies that provide comprehensive visibility, and enable informed decision-making, in order to optimising cash flow, minimise costs and manage risk in a transparent and efficient way.
1. Simplify confusing processes to gain moments of clarity
Effective risk management starts with integrating data from various sources within the organisation. By consolidating data from finance, operations, procurement, and sales, CFOs can gain a holistic view of the business landscape. This integration enables them to identify potential risks associated with inflation, such as rising costs, supply chain disruptions, or changes in customer demand patterns. With access to comprehensive and real-time data, CFOs can make informed decisions that mitigate the impact of inflation on the organisation.
A good first step is to unify travel, expense, and invoice solutions, so that finance teams can integrate and streamline operations and scale spend processes without adding additional resources.
2. Make spending decisions with data-driven accuracy
Once data is integrated, CFOs can leverage advanced analytics techniques to identify patterns, trends, and potential risks. Predictive analytics can help identify inflationary pressures, allowing businesses to proactively adjust pricing strategies or negotiate favourable terms with suppliers. Additionally, scenario modelling can simulate the impact of different inflation rates on the organisation’s financials, enabling CFOs to devise appropriate strategies for managing risk. By harnessing the power of analytics, CFOs can navigate inflation challenges with greater confidence and precision.
3.Driving business agility through automation
Facing a myriad of disruptors, companies in every industry are making strategic decisions aimed at remaining competitive in the market and with their people. Digitisation, standardisation, and automation will be critical as businesses focus on solving problems for their customers in innovative, lasting ways
AI technologies, such as machine learning algorithms, can analyse vast amounts of data to uncover hidden insights and patterns. And with automated, customisable controls, CFOs can keep their firm agile – re-adjusting spend controls to match the corporate travel and expense (T&E) policy whenever their business needs to adapt or pivot. Only then will spending insights allow them to review how policies impact business performance and continue to optimise cash management.
Making the maths work
In a business environment plagued by persistent inflation, CFOs play a crucial role in addressing the associated challenges. By rethinking how their organisations measure and manage risk, CFOs can enhance their decision-making capabilities and add significant value. The integration of data, advanced analytics, and AI technologies enables CFOs to build resilience, standardise processes, ensure compliance, and deliver insights to the entire enterprise. By making the maths work in the face of inflation, businesses can navigate uncertain economic times with confidence and stay on the path of sustainable growth.
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