Chatbots answer customer visitor questions or requests. While many rely on command-based functions, the better AI chatbots use artificial intelligence, especially NLP (natural language processing), and sentiment analysis.
Occasionally people refer to these bots as AI assistants, conversational interfaces, conversational agents, or even chatterbots.
Posting authentic online content from your brand or employees has proven to be an effective customer engagement and marketing strategy. Further, there is a wealth of data to show you how to reach customers with personable content.
Credit scoring is a statistical analysis performed by lenders and financial institutions to assess a person's creditworthiness for mortgages, credit cards, and private loans. Credit scoring is used by lenders to decide whether to extend or deny credit.
Traditionally, a person's credit score determined by credit bureaus is a number between 300 and 850 with 850 being the highest credit rating possible. As new types of lenders and insurers emerge, however, the traditional credit score becomes just one parameter joined with a large variety of alternative data that helps determine a person's creditworthiness.
Behavioral targeting is the process of marketing to people who are most likely to use your products or services based on their demonstrated behavior. This behavior may be online (for example, keywords searched, websites visited) or offline (location tracking data, for example).
Brand repositioning refers to the process of changing the associations that people have with a brand.
More than a superficial change like a logo redesign, a repositioning strategy represents a radical change in a company’s marketing and identity. Rarely do companies reposition themselves without great need.
Competitor analysis is the process of understanding your competition in order to succeed in the marketplace. With a proper competitor analysis model, you can benchmark your progress against more established competitors, identify your target market, and even anticipate new products or services from your competition.
Customer lifetime value (CLTV) is the expected profit that a single customer brings to a company over the course of their lifetime. CLTV represents a shift in emphasis from quarterly or annual profits to the long-term relationships with customers.
Nowadays, the abundance of data and the advances in Machine Learning and big data applications reduce the need for top-down segmentation of customers. Smart customer clustering based on many commonalities help companies better address customer needs to provide the right experience and divide resources efficiently.
Organizations must satisfy the unique demands of their customers. The good old days of mass marketing and predictions on limited mixture of products in one location are gone. Conversely, the use of artificial intelligence in inventory generates huge dividends to companies willing to reshape their supply chain orders.
This technological development results from the availability of massive amounts of real-time data now routinely generated by enterprise software systems and smart products. By collecting this data, organizing it, and interpreting it, artificial intelligence and machine learning have introduced an entirely new level of data processing leading to deeper business insights.
Everyone wants more leads, but the more we are able to generate, the harder it becomes to identify which of them are actually worth the time and effort spent in order to try to convert them. Lead scoring models let you automatically rank your leads in order of the perceived value each lead represents to your company. Resources for marketing and sales can then be distributed by the priority determined by lead scoring.
More than merely translation material into a target language, marketing localization consists of adapting your approach to the local culture. This includes website translation, currency conversion, and relationship building with local banks or distributors. Even product adaptation—making changes to the products you sell—can be part of a broader localization strategy.
Machine learning models are increasingly used to adapt material to local cultures. Translation, especially, lends itself to machine learning solutions.
Most if not all companies and organizations seek to establish themselves in social media platforms such as Facebook, Twitter, and Instagram in addition to their official website. Online and social media performance tracking is meant to analyze the effectiveness of a company's social media presence. Are they generating new leads? Are they promoting brand awareness? These questions are important to assess the efficiency of the use of these social media platforms.
An online recommendation engine is software that analyzes available user data to generate suggestions for something the user may also be interested in. Such engines are used in an advertising capacity to promote products or services or for the purpose of recommending similar content to the content the user has consumed in the past, such as in streaming services and online shopping services.
As opposed to customer segmentation which divides the market into groups based on demographics and purchase history, persona detection and segmentation creates more personal profiles in order to better understand potential customers using information about behavior, attitude and personal journeys.
Price segmentation is the practice of offering the same products or services for different prices based on who is paying. Examples of a price segmentation strategy include loyalty cards, coupons, and student or senior discounts.
Price optimization is the mathematical analysis by a company determines the response of potential buyers to different prices for its products and services. The aim is to meet a company's objectives of maximizing profits and growing and retaining a customer base.
In order to enter into a new market, businesses must have an effective product adaptation strategy. This strategy is essentially the knowledge of what part of a product or service must be changed in order to appeal to local customers.
Adaptation differs from localization in that the former changes only surface-level factors.
Sales forecasting is the system by which future sales volumes are estimated—at what price, during which time, and in which market. Product performance forecasting enables businesses to make informed decisions in both the short term and the long term. Machine learning software is continually improved, providing businesses with better analysis all the time—faster and more reliably than manual methods.
In the current era, consumers expect the firms they engage with to provide personalized service and offers. They believe that companies have the technological tools to analyze their specific needs and can perform this task with minimal effort, so businesses should develop such ability.
One may imagine that this kind of mass operation will need some resources and financial investment but by implementing artificial intelligence and automated processes, this capability can be readily available for any business.
Traditionally, personalization was focused on a set of rules based on existing data. The firms used to collect data in advance without any consideration for real time data but now better and much faster results can be obtained by using AI that allows businesses to conduct profiling and real-time analysis to optimize each conversion. This process is defined as Predictive Personalization and is driven by Machine Learning.
Promotional planning is the process of optimizing marketing tools, strategies, and resources to promote a product or service to generate demand and meet set objectives. Artificial intelligence (AI) can be used to effectively plan promotional events, measuring their outcomes, and adjusting as necessary to achieve growth.
Share of voice (SOV) refers to the amount of engagement your brand receives within your target market. It also specifies the sentiment behind the engagement—that is, whether people feel positively or negatively about your company.
The shelf is a dynamic environment, where shoppers select items purposefully and on impulse, where store owners showcase products to entice customers in the store and online.
Inventory management does not just entail having the right stock but also ensuring said stock was effectively sourced, stored, and sold at the right price, at the right time.
AI has been used to improve supply chain and demand forecasting for a couple of decades. Demand planning applications use data driven algorithms to take historical data and use it to forecast. Demand forecasting can include promotion planning or stock and sales forecasting. The machine looks at the forecast, compares it to actual shipments, and suggests alternatives and optimization options. Over time, many companies started doing more specific forecasting for specific regions, products or stores or for more granular points in time. Both retailers and their suppliers (CPG companies or 3rd party shipping and supply chain companies) use their data to help conduct automated decision making within the supply chain.
In today's global economy, supply chains include numerous partners, with services and sourcing managed across several organizations and in jurisdictions across the world. Corporations are increasing their use of third-party suppliers in the execution of key strategic imperatives and these third-party operations are becoming larger and more complicated as time goes on. Businesses should upgrade their risk management framework if they don't want to miss potential profits and saved costs.
Targeted marketing is a marketing strategy which identifies an audience that is most likely to buy a product or service and subsequently creates a marketing campaign designed specifically to advertise said product or service to the target audience, using advertisements and promotional messages. This allows different companies to hone in on certain market segments, creating a "specialty" and possibly lowering competition with similar companies.