Latest Digital marketing Trends

When we talk about intelligent retailing we talk about the technologies, today used by retailer and eCommerce seller to offer better pricing by optimizing the inventory. Intelligent retailing includes a whole ambit of technologies like Big Data, artificial intelligence, machine learning, new sensor hardware and varied solutions stemming from them. Dynamic Pricing and inventory optimization These retail trends are designed to enable dynamic pricing, markdown optimization and inventory optimization so that retailers can plan quantity and pricing of their products appropriately. Simply put, cost savings for the retailer. The predictive pricing solutions include usage of daily/weekly/monthly data and uses historical trends and current sales metrics to forecast best pricing scenarios to help the retailer in promotion planning and to determine percentage of discount per product per region. Predictive inventory management and cognitive demand forecasting solutions that were dem

Today marketers understandably tend to possess over purchases. Even if they understand an entire consumers journey leads up to a purchase, the actual sale is the tangible result of all their efforts and the thing that puts money in the exchequer. That means many ends up focusing on where that purchase gets made, either online or in-store. This is an important data point, in our research people preferred purchase certain things from online and some from store. But the truth of today shopper’s before purchase any thing they browse and research online whether they have intend to buy from store. In our research we talk some shoppers regarding their purchase journey about 60-80% people browse and research online and see the factors like features of the product, customer reviews, pricing & warranty before make any purchase. Omnichannel Channel Strategy Wins- In Some categories We talk about apparel, how you should buy something without trying it on? As in our research a

Every eCommerce seller knows that when it comes to selling products online, ads creative and content on that is the king. When consumers cannot hold a product in their hands, top-quality content can bridge the gap – through rich information, pictures, videos, and more. Optimizing online content serves manufacturers and retailers alike; but often, we still see product listings on the ecommerce sites that leave shoppers under-informed or simply uninspired. AS we talk some eCommerce sellers, they know well what does and what doesn’t speak to customers. Below are some common mistakes you look before you list your product on eCommerce platform. 1.        Research about products : You should spent some time by researching what type of products sell instead of jumping without the parachute. If you're jumping into the e-commerce space, talk to as many experts in the industry as possible, do throughout research, and assess your competition. 2.    Sticking to the basic

For advertisers, the changing media landscape means there are more ways to reach customers with effective advertising than ever before, with a steady shift to online formatting. At the same time, as per the market competition ad budgets are hardly grown but development timelines have been reduced. In this demanding new environment, advertisers and agencies need fresh approaches to testing ads effectiveness: Boost efficiency (cost and time) Leverage learnings across media Mine insights across and within ad campaigns Accommodate new and emerging ad formats Focus on what makes you different Design visually creative ad designs Your message should be clear Understand International nuances Use the wisdom of crowd before launch Targeting options available to you. Run of Network Options Relevance of Network Niche Publishers Device options as per your customers likely to use as per your product and service. Know your audience Advertisers now need earlier-stage,

Today business using big data & machine learning to learn about customers behavior. With customer behavior analytics, business is able to make data-driven decisions because they have an individual-level view of their customers. When business know exactly what customers want, what they do and look for, and how they may act in the future, they are in a better position to create personalized customer experiences and increase customer loyalty. McKinsey  found  that 50% of companies making use of customer behavior analytics are likely to have sales significantly above their competitors, 6.5 times more likely to retain customers, and 7.4 times more likely to outperform competitors in making sales to existing customers. Overall, organizations that correctly utilize customer behavior analytics are 19 times more likely to achieve above average profitability. If you want to enhance your business performance and make improvements in your marketing campaigns, then, here are some pra

As a marketer, chances are you’ve used consumer insights to understand what your customers want and then delivered relevant experiences to them. But have you ever used intent signals to predict what your customers want? Today, marketing technology allows you to do just that. The reality is the customer journey is nothing short of dynamic. As the journey continues to shift and change shape, it’s becoming harder for marketers to make sense of all the consumer intent signals people leave behind. Because as people look for what they need, they switch between channels and devices. They may conduct a research and saw the journey of the customer from start to end. Marketers have had to navigate these twists and turns by juggling first- and third-party data, probabilistic modeling, or remarketing. But all of that manual juggling simply won’t cut it. Today’s consumers expect more. They want assistance at every step. Therefore, as marketers, we need to be one step ahead of our customers —

As a business, you know how hard it is to keep up with customers today. People have become research obsessed for most purchases and expect brands to assist them in a personally relevant way at every stage of their purchase journey.   Machine learning is one automation tool that can boost your efforts to meet people’s high expectations. Machine learning can help to create automated marketing campaigns, at scale, that place the right message in front of the right customer at the right time at the right price, delighting people and delivering the business results marketers want. We talked  with top brands decision makers who have adopted machine learning to improve their marketing, we’ve found that the top-performing brands are applying these below rules and asking themselves these questions to achieve goal with automated marketing: Optimize your campaigns for growth : Machine learning is only as good as what you ask it to optimize. Top performers optimize the c

You can’t achieve the business outcomes without the right measurement. Today market is number  market. If you can’t measure it, you can’t do it. So, some years back, when people started talking about organizing their brand around the customer, I thought, “Yeah, but what does that  actually look like?” Fast forward to today: We’ve turned that jargon into a reality. Below are the questions put on the path to better measurement: A Better Strategy for Measurement Is your company set up to give you an aggregate view of the customer journey ? If your answer is the latter, I can guarantee you’re getting a ripped understanding of your customer, and you’re not set up to measure for growth. At the top level of your company, your business goals are to attract new customers _ engage them for long term relationships and delighting strategies ensure customers are happy, satisfied, and supported long after they make a purchase . Rather than individual channel teams, now you have two

Automation and machine learning technologies are changing the way marketers drive results for their customers and brands. But there’s still a significant gap between those who are just talking about machine learning and those who are taking action. For marketers looking to become leaders in their field, this is an exciting time. It’s a chance to make your mark, get ahead of competitors, and drive real results. To explore this shifting landscape, we partnered with the Massachusetts Institute of Technology Sloan Management Review (MIT SMR) to conduct a global survey and interview over a dozen executives and academics about their use of automation and machine learning technology and the results they’re seeing. Do more with your data Companies with appreciations to use machine learning have more ability to drill-down and see their KPI data in greater detail. This can lead to increased knowledge sharing and transparency, and help teams work together to make smarter , data-dr

Consumer behavior is the study of how people respond to products and services, followed by their marketing and selling. It’s of huge importance to managers because the focus on consumers is the key contributor to the marketing of business practice. Business who truly understand their consumer needs, can come up with better products and services and promote them more effectively. Today consumer expectations continue to rise and new behaviors are evolving. People are more aware turning to their phones for advice with the expectation of finding what they need right here and right now. Consumer behaviour study includes: How consumers think and feel about different alternatives (brands, products, services, and retailers) The behavior of consumers while researching and shopping How consumers reason and select between different alternatives How consumer behavior is influenced by their environment (peers, culture, media) How marketing campaig