The last time you had a great customer experience, how did you feel? When you last found a product that you truly, genuinely, loved, what was the sensation? Both of these things trigger reactions within us; deep reactions that – you would think – can’t be measured.
Or can they? Increasingly, organizations are looking to emotional analytics to help them understand their customers better and, therefore, to better meet their needs. Through understanding the emotional factors which come into play whenever they interact with customers, companies can construct a stronger, more effective brand profile.
The Engagement Yardstick
Content marketing is a common – and highly effective – way for an organization to develop a strong brand. The organization crafts a piece of content with genuine worth and value for the user. Then, they deploy that content in a prominent position online. The user comes along, examines the content, reacts on both a practical and an emotional level, and associates both of these reactions with the organization that posted the content.
Wait… hold up. A practical and an emotional level? What does that mean exactly? Well, if an organization posts a piece of content with tips to help users keep their PCs virus-free, the user will respond to the practicality – i.e. they will use the information or pass it on to someone who needs it – and then on an emotional level; “this company has really helped me out, they are good guys”, for example.
Both of these levels of reaction are key to brand development.
Organizations will often look directly at social engagement as a way to measure the public response to content. Positive comments, retweets, shares, clicks, new followers; all factors which indicate a strong reaction. However, as MarketingLand’s Erika Trautman points out, this cannot always be relied upon.
She explains that the above represent only surface metrics. To really get to the bottom of engagement, analytics must go deeper. Trautman advises defining more valuable metrics by which to measure engagement data. This could include quantitative metrics, such as sales or other actions derived from shares or clicks, user behavior following initial engagement, and proportion of new user engagement following the campaigns deployment, or even the qualitative data of user comments and reviews. All of this helps us to build a better picture of what is working and what is not working on an emotional level.
Emotional analytics is about more than simply measuring the reaction to content; it is about understanding the drivers and motivators which impel a prospect towards a purchase. These are the emotional triggers which drive engagement; get used to them, you will be seeing a lot of each other.
There are many psychological factors which push a prospect into action. These factors can then be harnessed within your brand to pull the right customers in, and to inspire action in prospects most likely to convert.
For example, a piece of content may introduce a fear factor, subtly playing on the prospects own fears and concerns. The brand is then introduced as a way to combat this fear.
Alternatively, the content may seek to build trust with the user. To do this, you must first understand what the ideal prospect defines as ‘trustworthy’ and then tailor your content to this.
Other emotional triggers include aspiration – in which content is deployed to act on the prospect’s desire to belong, or to upgrade their lifestyle – guilt, and enjoyment.
By utilizing these triggers, you can build a strong and highly effective brand, but in order to do this you must first understand your prospects. What do they react most strongly to? Which is the best approach to take? Emotional analytic techniques give you this information.
Once you understand your users, customers and prospects, what do you do with this understanding? The data needs to be molded into usable insight, certainly, but what form should this insight take?
Customer profiles. By fashioning the raw emotional data into a customer profile, we can ensure its long-term efficacy. These profiles give us a quick reference point which tells us what our prospects will engage with and how to strengthen our brand even further.
In effect, customer profiles are snapshots of our typical customers in each area of our business. When creating them, we start broad and general, and then we use the data we have acquired from emotional analytics to get ever more specific. The result is a life-like rundown of all the details pertinent to our customer demographic.
The profile can then be used to craft bespoke content pieces; each one tailormade to the nuance and idiosyncrasy of this particular customer profile. The result? Content which resonates deeply with a specific section of your audience, both on a practical and on an emotional level.
Some companies have been taking the whole ‘personalized content’ thing one stage further. Step forward, UK-based low-cost airline, EasyJet. In 2015, the carrier wanted to do something special for its 20th anniversary, so it turned its attentions inward to the data it had already collected. Using archived customer data, EasyJet sent out personalized emails, which had been generated automatically from these datasets. These emails took users on a journey through the places they had visited with EasyJet, creating a very special, bespoke effect.
You might think EasyJet could have achieved a similar result by simply blasting users with different destination images in the hope that some trigger a flicker of recognition. Possibly, but it would not have had the same effect. By taking the time to tailor the content to specific users – in the same way that Facebook does on certain anniversaries – EasyJet is fostering a profound emotional connection; this is tremendously valuable in attracting and retaining clients.
This is the future of emotional analytics. By creating personal narratives and journeys for our users, we are putting data insight directly to work in forging powerful emotional bonds with our customer-base. This, in essence, is the end-game of any brand strengthening strategy.
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