How Data and AI Enable Digital Marketing, Marketing & Advertising News, ET BrandEquity
[ad_1]
Representative image (iStock)Digital retail marketers face a rapidly changing landscape shaped by the emergence of data as the industry’s future currency. As the global economy becomes digital, shoppers are left with an exponentially growing treasure trove. Track your data.
Amazingly, most of the world’s data since the beginning of human history was created in the last two years alone. Unlike traditional currency, this resource is plentiful and seemingly endless, but it can be difficult to use it correctly. Still, it can be an advantage in itself. US retail media is growing at over US$10 billion annually as vendors invest in an ever-expanding retail media platform and capabilities. Much of the rest of the world has followed suit.
With the rise of e-commerce, it is increasingly possible to track every detail of shopper demographics, customer buying journeys, product inventory and content quality. Additionally, subscriptions and loyalty programs will enable digital marketers to track individual in-store behavior over time. Extensive digitization also means brands can better track their internal processes. To make the most of available data, digital marketers should pursue a holistic retail ecommerce management (REM) strategy. You need to master the 3 A’s:
1.Tally
2. Analysis
3. Action
Before brands can make smart decisions, they need to aggregate all available relevant data. For example, you need to track advertising spend across all customer and retailer accounts so you can easily compare omnichannel. In addition, internal data should not be trapped in various information silos that interact infrequently.
Instead, inventory should be an input to marketing decisions. Not integrating this data risks costly mistakes and missed opportunities. Having a single source of truth for storing and presenting all this data is essential. Shoppers, brands, retailers, and back-end supply his chain data should all be accessible through a single platform that can quickly aggregate and trend the data digital marketers want to understand.
Second, data must be analyzed continuously to better understand the market. Human-based approaches are too slow and imperfect for large retail brands. Too much data to analyze. Enter machine learning and AI. Using preset parameters, algorithmic retail ecommerce can uncover relevant trends and opportunities that employees may not be able to discover on their own. Savvy marketers can’t know every detail about their consumers, but they should have access to data and tools that can answer the questions they need to answer.
The final step is action. All data in the world is meaningless if it cannot be used. But as data proliferates, so does the number of potential decisions. For large brands, hundreds of small decisions need to be made and executed every day to stay ahead of the market in real time. Human-based efforts and processes may not be able to keep up with actionable steps that require so much data and analysis. The digital environment must be effectively managed using AI and machine learning. retail ecommerce strategy.
These tools should be based on preset parameters that align with your larger strategy or goals. Dynamic pricing, ad spend adjustments, and day-to-day processes like error detection and ticket submission should all be automated without human intervention. When these decisions are automated, marketing teams can focus on what people do best. That is, establishing and maintaining a larger vision that algorithms can automate.
How can brands take steps to leverage more data and machine learning in their retail ecommerce strategies? Here are five actions digital marketers can take now.
Review current data issues and software service providers. Look for opportunities to aggregate and combine functionality into one of her platforms and eliminate redundant services.
Invest in the right technology partner: If necessary, research the market to determine who is best positioned to process data and meet your organizational goals. Increase revenue by automating recurring tasks as much as possible.
Determine common KPIs to minimize disagreements. Many brands spend a lot of time in internal disagreements arising from analyzing their business using different metrics. For example, when evaluating marketing performance, should ROAS and share of voice be used? Determine common metrics that all stakeholders can respect in order to move the business forward.
Provide clear lines of communication within the company. Ensure key stakeholders across different departments of your organization are heard about your metrics, data, and goals. Communication must be continuously facilitated.
monitor the market. See how the market and competitors are reacting to your strategy and respond appropriately with both small tweaks and major overhauls to each campaign. Automation and machine learning are just as effective as the rules that guide them, and they need to be regularly updated in line with the market.
(Expressions are personal.)
ETBrandEquity met with Justdial’s Chief Marketing Officer, Prasun Kumar, to discuss all the attributes. Even today, Kumar feels that not all marketing channels necessarily interact with each other, making robust and accurate attribution difficult. He adds that even within the digital ecosystem, all platforms are inconsistent with each other, so marketers need to build assumptions so they can drive attribution.
[ad_2]
Source link
