Deep Learning: Where Does it Stand Currently?
A report by IMARC Group establishes that the niche of deep learning is predicted to grow at a staggering 40% CAGR in the period 2021-26.
The commercial world today is standing in an arena where only the businesses that have both – the muscle and the brains – to compete can survive. Competition for consumer acquisition is at its all-time high. Marketing tactics and strategies are evolving even as you read this article; in fact, marketing has taken on a completely new face.
With the entry of artificial intelligence into the marketing scene, the relationship between brands and their customers has completely morphed heavily into being a user-centric experience. At every stage in the sales & marketing funnel, right from creating awareness to generating repeat sales, artificial intelligence is at play in the form of deep learning.
Before jumping into the technicalities of deep learning in the sales & marketing funnel, let’s first understand what both these terms mean.
What is a Marketing Funnel?
A marketing funnel is a conceptualized representation of a consumer’s journey through a brand – from the point where the consumer first finds out about a brand, to the point where he purchases it. It has five major stages:
- Awareness, where the consumers find out about a brand
- Consideration, where he compares the brand with its competitor
- Interest, where he is interested in finding out the entire range of products of the brand
- The decision, where he is convinced he wants to purchase from the brand
- Action, where he makes the purchase
Marketing tactics evolve significantly as a consumer progresses through each of the stages listed above. These strategies need to be highly targeted, customized, and convincing if a successful sale is to be made, which is why deep learning applications are becoming exceedingly popular in marketing.
Let’s now understand what deep learning is and how it helps in marketing.
Deep Learning in The Marketing Funnel
The marketing funnel is a long journey and deep learning makes it possible to navigate through it without much error. But what is deep learning?
Deep learning isn’t just another fancy buzzword of the Gen Z century – it is a concept more advanced than machine learning and, at the same time, machine learning’s smarter “offspring”.
For the sake of clarity, while machine learning uses a set of algorithms to “understand” user behavior and improve over time, it requires human interference in case an erroneous value is returned. This is where deep learning differs from ML – it uses a multi-layered stack of algorithms that can learn from user behavior and correct errors without the need for human intervention.
Employing deep learning applications into the marketing funnel drastically improves customer experience with a brand for this very reason – when a brand knows what a consumer wants and builds his experience from there onwards, the journey through the funnel becomes very streamlined.
What is Deep Learning Used For?
In the sales marketing funnel, at each stage, deep learning finds a pivotal role. Let’s discuss that in detail.
One of the most important tasks in building brand awareness is targeted marketing and creating relevant consumer cohorts. Deploying deep learning applications in this stage of marketing helps to create predictive, intelligent models of pattern recognition that are in a league higher than what traditional machine learning or human efforts can create.
Personalization of advertisements is also scaling new heights with deep learning engines delivering highly focused, targeted content to consumers – a hyper-personalized experience that wasn’t possible before.
Creating Unique Value for Each Customer
Deep learning applications have made it possible to personalize even the mass resources (like websites) to deliver a truly tailored experience to the consumers. Based on search habits and product preferences, content on the website can be customized. Additionally, virtual conversation assistants powered by deep learning are now being deployed as initiators of conversation between a brand and its consumer.
Competition between brands is high. Getting a customer to convert requires a deep level of understanding of his problem, and providing a solution that addresses all his pain points. With the help of deep learning, it is possible to effectively map and synthesize a customer’s journey through the brand, and derive analytics from it that help to serve him better. This is the only difference between a successful conversion and a lost customer.
Enabling Customer Loyalty and Advocacy
In the long term, all brands aim to gain more and more returning customers. Looking at this from a different perspective, delivering a well-tailored experience to the customer is what gets them to return from the brand, as they seek to feel understood and catered for when they are out to make a purchase. Deep learning applications make it possible to stitch this journey together for the customer.
The satisfaction thus birthed from such a holistic exchange with a brand then goes on to create a customer that recommends that brand to more people.
To understand how smart algorithms help, in an example from 2017, Netflix saved $1 billion by using ML to display personalized recommendations to its subscribers, according to Forbes.
Deep learning applications have revolutionary implementations in every aspect of business – there is only the need to intelligently understand how to deploy and utilize it without getting overwhelmed by the ensuing data that follows.
As a digital shopping assistant, AskSid is poised to disrupt the online retail industry with its proprietary Retail AI Brain, a unique knowledge repository converting raw brand data into tweet-sized Q&As, product tags, intents, and utterances. This powers impactful shopping experiences and drives conversions across chatbots and voice bots, while simultaneously extracting deep customer insights, helping brands uncover new business opportunities.
Looking to deploy a vertical AI-based digital shopping assistant for your retail business?