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The Value of Real-Time Sentiment Analysis

by Erica Titchener, Global Head of Technology, Operations and Analytics Consulting, Alexander Mann Solutions

The value of a great employer brand has become more important than ever. According to research from Glassdoor, 11% of candidates would decline a job offer from a business with a bad reputation, even if they were unemployed.

External brand perception is a delicate commodity which can be strengthened or dismantled throughout the recruitment process. Whether your organisation gets this wrong up front through an overlong, mobile “unfriendly” application, or later on through a bad interview, getting better insight now into how candidates feel about their engagement with your organisation is essential. LinkedIn found that 83% of jobseekers say a negative interview experience can change their mind about a role or a company they once liked. And it works both ways: 87% say a positive interview experience can make them reconsider a position or business they once doubted.

An organisation’s employer and consumer brand are intrinsically linked, and the way a business attracts, engages and manages candidates will inevitably have a knock-on effect on their brand, and their bottom line, just as it does with customers.

How can businesses be sure that their candidates, whatever the result of the recruitment process, remain potential customers? In the consumer arena, a significant amount of insight is gained through customer feedback.

Today, talent acquisition functions rely on the collection of retrospective feedback, and by the time talent management teams are even aware of a problem, it’s far too late to take any valuable, meaningful action. To be effective, talent acquisition leaders need more immediate, actionable insights on candidate sentiment.

Success lies in collecting feedback in real-time at key stages of the recruitment process, so that successes can be celebrated and problems can be quickly identified and addressed. The mechanism needs to be digital, targeted and simple for the candidate, thereby increasing response rates, delivering more ratings and comments for automated sentiment analysis.

Organisations we’re partnering with have found that while the implementation of real-time sentiment analysis has been somewhat disruptive, the insight they’ve been able to collate has allowed them to make simple, targeted changes in the ways in which they engage candidates that have a real impact.

For example, a US Financial organisation using a real-time feedback mechanism received consistent negative feedback about interviews conducted within a specific area. Armed with this insight, they took immediate steps to ensure that hiring communities had the right training to help them understand their role as a brand ambassador and gave them additional practical guidance for interviewing. Following this initiative they saw improvement over time to an issue which may have gone unnoticed indefinitely if they’d not taken the time to make feedback simple to give and easy to analyse. This is critical as research from CareerArc has found that 72% of jobseekers who have had a bad interview experience have told others about it, either online or in-person. Our experience with other organisations has shown us that this kind of negative social messaging can be avoided if you have the information and the right structure in place to act on it quickly.

Providing a consumer grade experience to the recruitment lifecycle has become increasingly important, especially when considered within the wider context of the exponential advancement in the way we engage with technology in our daily lives. This, coupled with the inevitable culture shift brought about by digitally native generations moving into the workforce has meant that companies need to build agility into their talent acquisition functions, thus increasing their speed of adoption as technology, robotics and AI continually evolve the way in which we work and engage candidates. People now expect any online experience to meet consumer standards and can be put off by what they feel to be a “clunky” or disjointed process.

If you look at your own organisation, you’ll likely discover that your marketing teams have long recognised the value of great experience, and are working behind the scenes to track and respond to customer motivations and behaviours. Some may be leveraging advanced tools, such as Deloitte’s ‘Machine Learning for Customer-Sentiment Analysis’ offering – which pinpoints topics of interest to a target market and adapts messaging accordingly – demonstrating just how advanced the practice is becoming.

It makes sense, then, that similar technology should be harnessed by recruitment strategists to monitor sentiment, particularly when the stakes can be so high. The Society for Human Resource Management has found that 60% of candidates have quit filling out online job applications due to length or complexity. In today’s candidate-led market, we know that the most sought-after professionals will not necessarily be willing to jump through hoops. Talent acquisition leaders need data and insights to enable them to make the case for impactful change that ultimately benefits the wider business.

According to previous research from CareerBuilder, 69% of candidates are less likely to buy from companies which provided a negative candidate experience, while 9% said they will tell others not to purchase from businesses they have had a bad experience with during the hiring process.

Modern technology allows organisations to collect, collate and monitor the popular image of their brand as expressed through social media. Information provided by ‘listening’ technology – which aggregates sentiment on popular platforms – is arguably more honest and detailed than simply looking at feedback which is invited from the brand itself. Using this method, lexicon-based technology builds taxonomies through which words and phrases are isolated and categorised. This level of analysis is only possible through the power of automation, and the rise of machine learning means that this type of sentiment analysis is becoming increasingly accurate, but how can this help talent acquisition functions? It can be difficult for an organisation to tie the negative feedback directly to the route-cause making immediate, targeted action challenging. By bringing real-time sentiment gathering and analysis directly into the recruitment process, the ability to take immediate action grows substantially and becomes powerful when combined with other insights gathered through additional sources. It can directly, through evidence, support the business case for simple and larger scale change.

Requesting feedback directly and in real-time delivers current, actionable insights. By inviting candidates to feedback through a digital, consumer grade interface similar to those used by Amazon and other retailers, you’re providing an opportunity and outlet for them to share negative sentiment directly with you which they would not otherwise have been provided had you not a) prompted them and, b) more importantly, made it simple for them to do so. If you’re able to follow up with them immediately to make things right, imagine the impact this has on their perception of your organisation.

The power of big data today means that we now have unprecedented access to real-time information relating to experiences, and through this, the ability to obtain a broader understanding of how this can ripple throughout a business – and the results can be shocking. When Virgin Media discovered that 18% of rejected candidates were also Virgin Media customers, the firm dug a little deeper and found 6% of these disgruntled candidates cancelled their monthly subscriptions costing the company £4.4 million per year.

Case studies like the one from Virgin Media should be an eye opener for other organisations. Enabled through automation and technology, real-time sentiment analysis offers organisations a chance to bring humanity back into the recruitment process helping talent acquisition leadership in planning future strategies which put people front and centre.

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