Improving Talent Experience with AI

Improving Talent Experience with AI

Artificial Intelligence and Machine Learning have brought about revolutionary growth for various industries- be it retail, pharmaceuticals, advertising, travel or finance. AI has made businesses customer-responsive, the most common applications being chatbots and virtual assistants.

Given that talent engagement initiatives have led to 26% growth in revenue for organizations according to reports, it is no surprise that AI has made its way into the HR strategy of more than 22% of the organizations surveyed. AI is the foundation for providing stellar talent experience, and if you are an HR manager, it is time you think of AI as your friendly new team mate – one that is going to help you manage hiring, onboarding, engagement, evaluation and retention more efficiently than existing HR models and practices, that too at a pace never seen before.

AI can be a game changer at every step along the Talent Life Cycle:

Searching the right candidates

Companies have typically spent a ton of time and effort in finding the right candidates on the internet. With AI, it is now possible to automate the search, i.e. match employee skills with role and company requirements, and reach out to gauge their interest, significantly cutting down time spent by recruiters and improving interview-to-hire ratios.

Acquiring the right candidates

AI goes a step further and helps you go over every application, scan it for suitability, and hence weed out the least-fit candidates. Some platforms are able to filter out over 75% of the applications, allowing recruiters to focus on the best profiles. Many companies are now using AI to analyze video-based interviews to read the fine print, i.e. assess facial expressions, judge attitude and fitment etc.

On-boarding

Statistical reports indicate that employees who are brought onboard using a well-designed onboarding program are 58% more likely to spend more than three years with the employer. New hires need to adjust to a whole new environment, and often need a lot of hand-holding to settle down, which is not always possible for HR managers to do. This is where AI takes over, by designing personalized onboarding programs that ensure employee satisfaction.

Talent Engagement

Gone are the days when the HR team could host an annual feedback survey to get a sense of employee satisfaction. It is expected that the leadership will keep a tab on the pulse of the organization in real-time, and address concerns immediately. Using AI, organizations now use pulse surveys to monitor the “mood” of their talent, identify geographies or teams that are under pressure or stress by monitoring the sentiment of their oral and written communication, and intervene accordingly.

Gordon Bethune, former CEO of Continental Airlines and the man credited for turning around the fortunes of the airlines, couldn’t stress enough on engaging with talent and valuing their opinions, emotions and feedback. He said “Treating your employees well is the right thing to do—and it’s good for the bottom line.” In fact, he regularly did a voicemail to update his teams on what is going on with the organization, and they could voicemail him back with their feedback – no judgments applied.

As organizations learn to leverage AI in the hiring and talent management process, it is important to think about the value AI can add by capturing talent expectations. What is it that your talent wants improved? What irks them daily? What makes them walk in to work with a smile? Without knowing what is important to talent, and by how much, it is hard for HR managers to fully capitalize on AI-powered HR tools.

OSG is at the forefront of developing technology and products that solve complicated business questions. Talent Success, OSG’s talent management platform packages advanced technology and behavioral analytics in an easy-to-use, intuitive platform to provide you with customizable question banks. Talent Success helps you gain deep insights into your employees’ challenges and motivations to get a real-time pulse on their state of mind at work. Talent Success enables you with employee-centricity and helps you make the right strategic decisions to become the organization that everyone wants to work for. At OSG, we rely on an extensive Talent Engagement Survey that keeps us relevant and an employer of choice, year on year. Read more about our survey here.

We hope this information has been interesting and valuable to you. Please, feel free to share it with colleagues and other people in your network. We welcome discussing this topic further with you and understanding your specific challenges

 

OSG Steps to Success

OSG is a “catalyst” that helps our clients be the best at decoding their customers’ decisions. Our clients have seen a minimum 20% improvement in customer engagement by implementing smart insights delivered using our behavioral analytics products.

From Cruise Control to Self-Drive: AI and its impact on Customer Experience

From Cruise Control to Self-Drive: AI and its impact on Customer Experience

I cannot wait to get myself a car that drives me around without a care for Bangalore traffic jams. If you’ve ever driven in this city, you will feel for me. How cool it would be to read a book, finish email responses, catch up with family, or even nap, while my futuristic smart car deals with narrow lanes, ill-mannered drivers, jay-walkers, and other such daily annoyances.

A decade or two back, this was the stuff of sci-fi movies. Truly, even self-parking and cruise control were considered revolutionary! Look where AI has brought us!

AI based technologies have touched all industries and provided us with the ammunition to disrupt the way customers interact with products at every stage of the product life cycle. We will soon see a generation that has only seen monthly groceries being ordered by their living-room concierge- Alexa. Whatever happened to the friendly neighbourhood grocery store? Alexa interprets more than 15,000 commands swiftly and is only getting better by the day.

According to a leading industry report, 62% organizations will employ AI in their daily operations in some form or the other by the end of 2018, and AI will be a market worth $47 billion by 2020. The most common form of AI is chatbots. We have all interacted with chatbots while trying to complain about some product or the other. Believe it or not, in a recent survey, 27% consumers said they weren’t sure if their last conversation with a “customer service representative” was with a human or a bot.

From a customer-service perspective, there are three things bots can do right now-

  1. Manage all the simpler queries that come into the system by way of automated responses
  2. Prepare agents better for what is to come- by understanding customer purchase history, their grievances, their mood and tone etc.
  3. Routing queries to the right customer service teams, minimizing wait time and frustration a customer typically faces

However, the role of AI doesn’t stop at customer service. By using AI along with behavioral analytics, organizations can truly extract the best from AI powered CRM tools. Behavioral analytics help you understand the drivers of customer choice, i.e. what is important to customers and by how much. Thus, if AI is employed the right way – in combination with behavioral analytics – it can assist organizations in creating smart, easy to use, informed customer experiences at every step along the customer journey. Right from identifying the right marketing channels and personalized messaging to creating awareness among customers, designing nudges that move them from consideration to purchase, pursuing cross-sell and up-sell strategies that increase the share of wallet and repeat purchases, to identifying customer behaviors that indicate possibility of churn, and finding ways to prevent that, AI can generate high-impact personalized customer insights that change the game for organizations. The result is comprehensive, innovative and personalized customer journeys across channels, that automatically lead to higher engagement and sales.

A simple example is the shopping experience offered by Black Diamond, a ski-equipment retailer. Black Diamond does not depend on visitors browsing on tonnes of products displayed on their website. Instead, by understanding a customer’s past purchase history, ski-locations, weather conditions and other such important customer choice data, they suggest the right products for their visitors, quickly converting abandoned carts to orders.

In a nutshell, AI combined with behavioral analytics will:

  • Take over mechanical customer queries, allowing employees to focus on more complicated and strategic interventions and solve for customer concerns quickly
  • Provide more personalized experiences to customers, leaving them with positive experiences
  • Store vast amounts of data and make sure organizations are learning from it
  • Create fulfilling and long-term customer relationships

Therefore, a state of the art customer journey analytics platform powered by AI and ML that goes deep into understanding what matters to your customers is the key to using AI to its full potential. OSG’s products powered by our AI based big data analytics platform, OSG Dynamo™ uses AI and Machine Learning to get to the root of understanding what personalized behavioral triggers can help customers stay motivated and engaged with your products and services throughout the customer life cycle.

A global e-commerce company has seen 30% improvement in retention with OSG’s AI-based products.

We hope this information has been interesting and valuable to you. Please, feel free to share it with colleagues and other people in your network. We welcome discussing this topic further with you and understanding your specific challenges.

About OSG

OSG is a “catalyst” that helps our clients be the best at decoding their customers’ decisions. Our clients have seen a minimum 20% improvement in customer engagement by implementing smart insights delivered using our behavioral analytics products.

AI with no EQ? Using Machine Learning as Training Wheels to Humanize AI

AI with no EQ? Using Machine Learning as Training Wheels to Humanize AI

In December 2016, a customer of Lemonade Insurance Company hit ‘submit’ on an insurance claim for a $979 Canada Goose coat. Approximately 3 seconds later, Lemonade’s claims bot – AI Jim had reviewed the claim, cross referenced it with the policy, ran 18 anti-fraud algorithms on it, approved the claim, sent wiring instructions to the bank, and informed the customer that the claim was closed.

 

However, not all chatbot experiences are like the Lemonade experience. Despite the sudden surge in chatbot usage, most of us would have had clunky conversations with chatbots on retail or financial services websites.

These include:

  • A poor user experience e.g. not understanding the dialect
  • Confidence in the product offering dipping
  • Provided us a good reason to go somewhere else that offers a similar product
  • Being redirected ultimately to a call centre, which is not what we wanted to do in the first place
  • So why are chatbots today not so smart?

Many retailers are embracing chatbots for the sake of chatbots – which in most cases is unlikely to yield any meaningful results. Retailers need to integrate chatbots in ways that interest consumers and make their shopping experience more personalized and entertaining to their needs. It’s all about working the goals of a consumer once that interaction happens, which is often not planned effectively with any chatbot integration.

The key issues chatbots battle with today are:

  • They use historical data gathered from your CRM, social feed etc. to attempt personalization
  • They are unable to learn in real-time. This means chatbots cannot follow live requests being made by a customer in a chat
    For most organizations, chatbots are insufficiently trained. They cannot understand things like human expressions of frustration or delight, acronyms etc. and thus end up giving inappropriate reactions to situations
  • Contrary to the perception of an automated service, chatbots need continuous tweaking and monitoring to get the best from business goals, which in most cases change at a rapid pace

Why does this happen?

Often, there is a trade-off between the best technology, speed of integration, & actual consumer POS requirements. Without understanding the core needs of their consumers and what drives their purchasing decisions, many retail and financial services organizations are being shaped ineffectively by the ‘potential’ of messaging apps, nudge technology and chatbots as the future for improved customer retention and churn rate.

A frantic race to full automation and the AI ‘blockchain dream’ is also to blame. Many organizations want to use chatbots to connect with customers in as many ways as possible, without thinking of the financial implications, technological dependencies and consequences. For example – designing sophisticated chatbots that:

  • Give out retail advice and product usage information
  • Award frequent users with discounts and loyalty benefits
  • Assist with shipping and logistics
  • Provide bi-directional marketing, i.e. give out information about the product to the consumer, whilst also simultaneously collecting information for market research through surveys and feedback

Emotions run deep in every human interaction and are unfortunately ignored. Deciphering these human emotions by way of studying voice modulation, facial expressions, text tonality etc. can reveal a wealth of information that can add context to a customer interaction with a chatbot and make the interaction more fulfilling. Only if AI has the capability to empathize with users’ feelings and learn in real-time about what the customer wants can it design the perfect responses, leading to outstanding user experiences.

This means that organizations must-

  • Ensure that chatbots quantify what matters to customers when making a purchase decision, and by how much
  • Ensure that chatbots can determine a customer’s emotional state

How can OSG help?

OSG uses its proprietary trade-off methodology ASEMAP™ to let customers prioritize benefits that are best suited to nudge customer behavior for each customer. By using a combination of cognitive analytics (historical data that looks at the “who” and “what” behind customer decision making) and future looking behavioral analytics (that go beyond traditional analytics to identify the “how” and “why” behind customer decision making), OSG can train your chatbot to learn in real time what matters to your customers. Our big data analytics platform OSG Dynamo™ can use text, tone and voice analysis to understand customer sentiment, helping you to humanize your chatbot during an interaction.

This helps you deliver a superior chatbot experience designed around a customer’s current and future needs. Write to us at website@osganalytics.com to learn more about our products!

 

OSG Steps to Success

OSG is a “catalyst” that helps our clients be the best at decoding their customers’ decisions. Our clients have seen a minimum 20% improvement in customer engagement by implementing smart insights delivered using our behavioral analytics products.