Future Of Consumer Marketing

This is a new series on Consumerism and technology. Amazon Go stores are open now which shows a staggering feat of technology. Understanding consumer pain points is key to acquiring customers. Till now companies used search results and text to model consumer behavior pattern. Now recognizing patterns in video is easier and gives more insight to buying preference. Thanks Listening.

Marketing space is changing with the advent of voice and AI. Placing an ad on Facebook or on social media isn't enough. Its about finding patterns in your data and what your consumer prefers.

Consumers are looking for better option and leave lot of information that businesses aren't picking up when they shop around.

Consumers react to pricing and other variables in the economy. By gauging those changes their behavior can be influenced to buy more products. With machine learning the advantage evaluating factors that can affect sale is a big win. Better analysis leads to better solution.

Pricing is a big variable in analyzing consumer demand. Factors that needs to be considered are Fuel prices, basket of 150 products that are used by the consumer on a monthly basis, inflation, CPI, Unemployment, new movie, holiday season, insurance renewals, healthcare, etc. These variables stifle capital that could have been spend in ecommerce or your product. Demand is predicated on these variables as well.

Voice platform is pretty new and has the potential of android market. World is moving from text based engine to a voice based.

Amazon recently introduced subscription for alexa skills. That signifies a big volume of customers using the platform. Apparently amazon owns 70% of market share in voice space through strategic partnership, Acquisition and open sourcing. They acquired customers through every move.

Ecommerce sites could recommend products of search results most clicked or add to cart product to consumer thereby enhancing sales. Finding what the consumer wants is the game.

How search results are arranged and position of the products matter. They can arranged based on best seller and most click. Positioning of products in website. Ranking product based on how often consumer react to search

Having a great offer and pricing influences customers but lack of capital stifles them. The way around for retail, Grocery and ecommerce store is to have a strategic partnership with credit card companies to give cashback and offers on credit cards so it entices the customers to use it today to grab the advantage and pay back later.

Consumer react to every offer, discount and pricing differently. So analyzing their behavior helps to evaluate sales and identify new preference of the consumer to recommend product that will bring value to consumer.

Demand is dependent how consumers react to different variables that affect them daily from Fuel prices, pricing of basket of products that are purchased weekly like Grocery and food, unemployment, CPI, availability of capital - Credit card offers and cashback.

Subscription model to discover food taste by sending 5 to 10 curated food products. Recognizing pattern by which consumers react with machine learning models to curate food and identify taste buds & change in taste over a period of time. This opens up platform to recommend restaurants that might have similar taste or complimentary one.

By taking point of sale data and factor that influence customers like fuel price, CPI, unemployment, climate, promotion, depth of discount, pricing etc we evaluate demand and inventory requirement with higher accuracy for perishable products that has a shorter shelf life. Overstocking will not work here, so good model to evaluate metrics is needed. Machine learning has a great solution

Consumer behavior analysis enhances sales for ecommerce environment. Trying different variables helps in finding consumer behaviors.

Personalization is about finding patterns in the consumer buying. Optimizing search results based on buying and click patterns. Finding new consumer preference to enhance sales.

Conversion rate has become the key variable to winning in ecommerce. Personalizing search results and product recommenders are winning strategy to enhance sales.

Voice technology is taking off big. Better interaction with your customer. There are numerous problems that can be solved with voice.

AI can take multiple variables that affect retail operation from pos data to weather to estimate demand and inventory with accuracy. This enhances supply chain operation reducing delivery time.

AI has proven to be a great tool to recognize patterns. By taking web analytics machine learning model can identify potential customers and interact with them through chatbots. Personalization is key.

Businesses rely on distribution to sell through. Product recommender system gives insight to consumer buying pattern. Its a big leverage to sell other products by finding consumer interest.

Voice tech offers lot of enhancement to daily operations of the consumer saving time and money by finding best offers & Low cost providers. It helps you find a new taste or music. Enables multitasking

First mover in the marketplace to identify the consumer preference will acquire customers. It comes down to how well you know your customer and their preference and factors that influence them to buy

Omnichannel management is key to optimizing retail store operation. Machine learning models are good at enhancing predictive demand cycle and recommender system to enhance sales.

Retail stores need to attract the customer to the stores. That requires identifying consumer preference and factor that influence consumer like pricing, discount, coupons, trends & bundle products.

Legacy software are good at enhancing dataflow. AI is about predicting sales, inventory and enhancing sales by analyzing consumer preference and pattern of buying

Voice technology and IoT will enable a interconnected world. Every device will have some kind of voice technology that will make customer experience better. Getting on the voice platform is the game.

Insurance sector has lagged innovation. With the advent of AI, the underwriting & claims process can be made efficient by reducing the time taken and better accuracy of prediction.

Chatbots market has grown significantly and many of the customer care problems have been resolved by chatbots. It all comes down to the creative of the individual in solving the problem with chatbots.

People are attracted by different variables in their career. Big data helps in finding factors that influence hiring of a great talent. Not everyone is looking for a great paycheck. Career path...

AI models are good at forecasting claims for Insurance companies. This helps companies to allocate and evaluate patterns in which the events occur. Provide education to consumers to avoid it.

Creating a podcast on Amazon alexa flash briefing will attract more audience. As it's listened to on a daily basis. Marketing should produce high value content for customer to attract and run some ads

Product recommenders help in recognizing consumer preference and demand. They provide insight & probability on products that haven't been purchased by the consumer. Sending a personalized product.

Voice technology is gaining traction fast. Amazon opened up interaction of voice in any device that has speaker and reciever. Every device in your home will talk to you to make comfort.

As the voice platform expand recommender systems are going to be deployed by every stores and business to personalize recommendation its the future of communication and sales.

As retail stores gear up for holiday season. Identifying customer preference is key to win customers in a highly competitive environment. AI enhances manufacturing operations, reducing defects.

By analyzing every variable influencing sales and customer preference, the probability of sale can be enhanced. A 10% increase in sale week over week when compounded yield big numbers. New preference.

AI has lot of application in the manufacturing sector. Enhancing the line of production by reducing uncertainity in demand. With IoT the potential of AI is be unlimited. It gives a massive boost.

Manufacturing and supplychain operation can be enhanced by the use of internet of things and AI. IoT gives real time info on change of inventories and AI can predict patterns and requirement.

Adding artificial Intelligence to sourcing, Procurement, Supplychain, Warehouse Management, sales, Product recommenders will optimize the retail operation to the next level. Lower price points.

Retail shopping experience will be transformed with Augmented reality as real time experience of object can enhance sales, reduce return rate. Its all about giving a great shopping experience.

Long term use of AI enhances sales, reduces sourcing cost, supplychain and inventory management. Banking benefits increased sales through pattern recognition and mitigation of risk on default rate.

Retail sales depends on customer acquisition and loyalty. Using AI will increase the probability of sale. It helps in reducing the sourcing cost, effective management of logistics & Inventory.

Next 3 months are crucial for Retail&Insurance companies as they gear up for increased customer traffic. Its important to add AI & recognize patterns in customer behavior to personalize recommendation

Voice technology holds the future of consumer marketing. As the consumer interaction is already explode. It's time businesses get on Alexa, Siri and Home to market their product and sell.

Credit card financial institution do provide ton of offers to attract customers to use the card. Product recommenders are well fit to do the job of enhancing sales by finding pattern of spend made.

By understanding the customer preference & pattern of buying products, personalized recommendation could be made. Pricing analysis helps in increasing the average order along with bundling of product

Long term prospective for insurance looks bright by using AI. AI can optimize underwriting, actuarial policy creation, claims, customer care, sales and Marketing. Customer behavior is key variable

AI has the potential to optimize any event that show a pattern of movement. Human DNA is one of the hardest combination to recognize pattern.AI is standing up to the challenge.

Retail stores get ton value by using AI. Predicting seasonal demand and pricing, Sourcing Product cost effectively, and customer insight. These data can be leveraged to expand sales.

Insurance sector can benefit from product recommender system and AI. They help in reducing the underwriting and claims process time. Product recommenders enhance sales by analyzing customer pattern.