Building Your Organisation’s Brand With AI

Rajan Nagina Jun 13, 2022

“Harley-Davidson used artificial intelligence to increase New York sales leads by 2,930%. They were also able to predict which ad copy and visuals would resonate with the customers most likely to buy.” HBR. This is just one of the examples of how artificial intelligence (AI) empowers brands to generate ROI, and build brand loyalty and authenticity while enhancing customer experience.

Enterprises across industries generate data in large volumes on a day-to-day basis. AI helps businesses in converting this data into meaningful insights and creating a favorable impression in minds of customers.

Let’s dive deep into how AI/ML can help in enhancing your organisation’s brand.

Understanding Customer Behavior

A McKinsey survey found that at the banks with the highest degree of reported customer satisfaction, deposits grew 84 percent faster than at the banks with the lowest satisfaction ratings.

To strike a chord with customers, it is crucial to understand how your customers think and feel about your products and services. Online mentions and brand reviews are not enough for you to understand customers’ brand perceptions. Customers’ sentiments must be analysed, which is a complex process. AI/ML provides you with powerful tools for sentiment analysis. Customers’ sentiments are captured in terms of polarity, which indicates a positive or negative customer emotion, and magnitude—measuring the strength of the customer emotion. Natural language processing (NLP) deciphers human interactions and feelings through various channels, including feedback forms, customer tickets, chats, social interactions, product reviews, and in-person interactions. Sentiments captured can help you understand true customer perceptions and then create strategies to improve them.

Creating Personalised Brand Experiences

Customers have an innate expectation of being understood and delivered just the right service or product. Per a Deloitte report, 38% of home insurance customers, 40% of health insurance customers, and 48% of motor insurance customers are willing to track their behaviour and share data with insurers for a more personalised premium.

AI/ML allows you to create a recommendation engine that can influence customers’ buying decisions, provide a filtered list of curated products and services, generate personalised offers, and create cross-sell opportunities encouraging users to view other products from the company. You understand your customers better and can predict their changing preferences, thereby tailoring advice and recommendations, which in turn increases brand engagement.

Designing Effective Marketing Campaigns

Brands create marketing campaigns to raise awareness and convert prospects into customers. AI makes it easier to segment and target the audience according to above-the-line (ATL), below-the-line (BTL) and through-the-line (TTL) marketing strategies. AI-driven market segmentation removes human biases, understands hidden patterns in data, automatically updates segments in a rapidly changing market, and is also scalable. Campaigns become more effective if the segments are accurate, leading to more conversions. This improves productivity, and effectiveness, and ensures a better return on investment (ROI).

Enabling Contextual Marketing

It is an online marketing strategy model, wherein people get to see targeted advertisements based on their searches, buying, and behavioural patterns. For instance, if someone searches for a property loan, ads from a similar category will be visible on the subsequent online browsing, which amplifies conversion rates.

Another powerful use of AI-based contextual marketing is the advertisement being relayed through over-the-top (OTT) media channels. Starting with TRPs and now with OTT channels gaining popularity, AI helps understand the context of the content relayed to the viewer and associates a relevant advertisement in a bid to enhance the effectiveness of the campaign. The key focus behind contextual marketing is to be able to relay advertisements to the customers for the product or services they are already inclined towards.

Ensuring Better Budgeting

Marketing mix modelling (MMM) helps measure the effectiveness of various marketing initiatives. Typically, MMM has three contributors, including:

· sales generated directly because of marketing activities, base drivers

· sales generated due to historical brand equity, and other drivers

· accumulated brand equity in a specific period directly due to sustained marketing activities

AI/ML can analyse your sales, spends, customer acquisition, sentiment data, and more to suggest the right marketing budget allocation, thereby ensuring better ROI while minimising chances of overspending.

The Final Word

AI goes a long way in understanding your customers, leveraging the available data, and creating the right models, thereby enhancing your brand and improving customer longevity.

*The author is Rajan Nagina, Head of AI Practice, Newgen Software