RESOURCES

All TECHNICAL terms EXPLAINED

Account Management

Account management: Account management is the process of nurturing a company’s customer relationships through dedicated organizations, processes, services, and tools. The long-term goal of account management is the maximization of a customer’s lifetime value.
Account plan: The account plan, sometimes also called customer development plan, is a systematic tool for the strategic analysis of a customer and their decision-making process. This analysis enables selling organizations to define goals, strategies, and actions to retain and grow the account.
Account sponsor: The account sponsor is typically a high-level executive who supports the account manager in the strategic management of a customer. As such, the account sponsor provides the necessary budget and resources, mediates potential conflicts, and represents the significance of that customer at board level.
Account team: Account management requires the successful cooperation of an interdisciplinary team of experts from various functions such as sales, business development, marketing, product management, and customer service. The (key) account manager is the central interface that orchestrates all activities within the team.
Buying center: A buying center is comprised of all members of an organization who are involved in the buying process for a particular product or service. A strategic analysis of the different functions, roles, goals, and relations as well as decision-making processes amongst individual stakeholders enables selling organizations to improve stakeholder engagement and negotiation.
Customer churn: Customer churn, also known as the attrition rate, is the percentage of customers who stop doing business or stop using a company’s products or services during a given period of time. Specialized customer churn management systems explore the reasons for attrition and can predict impending customer churn based on customer behavior.
Customer life-time value (CLV): The CLV enables a prediction of the net profit generated from the entire past and future relationship with a customer. This KPI is commonly used in account management, as all investments into a client relationship must ultimately pay off in the form of increased long-term value from this customer.
Customer loyalty: Customer loyalty is the result of a positive customer experience and manifests itself in the predisposition to engage with a company, repeatedly purchase and use their products, as well as refer their brand.
Customer retention: Customer retention refers to the activities companies use to decrease customer churn. While customer retention describes the abilities or actions of companies to prevent customers from switching to the competition, customer loyalty describes the behavioral predisposition of a customer to do business with a company.
Customer satisfaction: Customer satisfaction is a concept aimed at measuring the feelings, emotions, and attitudes customers have towards a company’s products, services, and capabilities. Common ways to measure customer satisfaction include the Net Promoter Score (NPS) and the Customer Satisfaction Score (CSAT).
Cross-selling: Cross-selling is the process of marketing and selling additional products or services to a customer that complement the products they are buying in order to increase revenues. In practice, cross-selling is often realized through bundle pricing.
Engagement plan: An engagement plan translates the strategic insights from an account plan into operative customer measures and actions. Engagement plans typically include stakeholder-specific actions and communication measures aimed at building trust, nurturing relationships and improving customer satisfaction.
Gatekeeper: A gatekeeper controls the flow of information into and within a buying center by actively filtering and selecting the forwarded information. Even though a gatekeeper’s involvement in the buying process is indirect, they have a significant impact on the buying decision. Common gatekeepers are secretaries or assistants.
Hit rate: This KPI measures the ratio of submitted commercial offers to received customer orders. As such, the hit rate provides an indicator of the strength of a company’s customer-specific value proposition and resulting sales efficiency.
Key account manager: Key accounts are typically the biggest and most valuable customers of a company. Compared to traditional account managers, key account managers are in charge of a smaller number of strategic accounts that are organizationally more complex to manage but also yield a greater value potential for the company.
Net promoter score (NPS): The NPS estimates a customer’s satisfaction based on how likely they are to recommend a company or a product on a scale from 0 to 10 at various stages of the customer journey. It is calculated by subtracting the percentage of detractors (scores 0-6) from the percentage of promoters (scores 9-10).
Share of wallet: This KPI measures the share of a selling organization in the total purchasing volume of a customer. This metric is often used in account management as it indicates the competitive strength of a company for a given customer and product compared to other different suppliers.
SWOT analysis: A SWOT analysis is a strategic tool to assess the Strengths, Weaknesses, Opportunities, and Threats of a company or a single product or service. As this analysis can also be carried out for single customers, it plays a central part in strategic account planning.
Value proposition: The value proposition explains the major benefits a company promises its customers with a particular product or service. As such, it explains how the use and features of their products or services address their customers’ problems, wants, and needs.

Customer Journey Excellence

Chatbot: A computer program designed to simulate conversations with human users, typically used for customer service or information retrieval.
Customer Experience: The overall perception of a customer’s interactions with a brand, encompassing all touchpoints and emotions.
Customer Journey: The process customers go through when interacting with a brand, from initial awareness to post-purchase engagement.
E-Commerce: The buying and selling of goods and services over the Internet or electronic networks.
Firmographics: Demographic characteristics used to categorize companies, such as industry, company size, or revenue.
Focus Group: A qualitative research method in which a small group of individuals is gathered to provide feedback on a product or service.
Geofencing: A location-based technology that creates a virtual boundary around a physical area and triggers actions when a mobile device enters or leaves the area.
Hyper-Personalization: Tailoring marketing messages or product offerings to individual preferences or behaviors using advanced data analytics.
Journey Mapping: A visual representation of the steps and touchpoints a customer goes through when interacting with a brand, used to improve the customer experience.
Kanban Board: A visual project management tool used to track work progress and optimize workflow efficiency.
NFC Tag: Near Field Communication technology used to wirelessly transmit data between devices when they are brought close together.
Pain Pleasure Gap: The finding that customers tend to remember two moments in their buying journey in particular, the peak and the end, suggesting that when a high follows a low, the peak is perceived as much more satisfying.
QR Code: Quick Response Code, a two-dimensional barcode that can be scanned with a smartphone camera to access digital information or resources.
Survey: A research method used to collect data from a sample of individuals to gain insights or opinions on a specific topic.
Touchpoint: Any interaction between a customer and a brand, product or service during the customer journey.
Virtual Reality: A computer-generated simulation of an environment or experience that allows users to realistically interact with and explore virtual worlds.

Customer Segmentation

Artificial intelligence: AI is the ability of a computer to perform tasks commonly associated with intelligent beings. Through the use of intelligent algorithms, which can discover patterns or learn from past experience, businesses processes can be automated and optimized.
AI-based segmentation: Leveraging intelligent algorithms for the purpose of customer segmentation removes inherent human biases and can help find hidden patterns in customer data that humans may be unable to spot. AI-based segmentations are more dynamic and scalable than traditional segmentations.
Cookies: Cookies are text files containing small pieces of data that are stored on a user’s computer by his web browser. There are different types of cookies serving different purposes, from the proper functioning of a website, to the identification of users, and the personalization of browsing experiences.
Cluster analysis: A cluster analysis is a statistical technique used to group objects with similar characteristics based on the observed values of several variables. Common business applications for cluster analyses include the segmentation of markets, customer portfolios, and sales transactions.
Customer care framework: The term customer care framework describes the set of guidelines that a company adopts to serve a particular customer segment or a particular customer. These guidelines encompass for example the resources, service levels, or commercial terms that are to be adopted for a given customer.
Customer intelligence: Customer intelligence describes the process of collecting, contextualizing, and analyzing data regarding customer characteristics, needs, and behaviors. Customer intelligence enables organizations to extract actionable insights from customer data in order to enhance customer understanding and long-term value creation.
Customer relationship management (CRM): CRM is a strategic approach for the planning, control, and execution of all customer processes, relationships, and interactions within an organization. The implementation of a dedicated CRM software is an important instrument to manage the entire end-to-end customer life cycle.
Customer segmentation model: A segmentation model describes the rules through which customers are scored across a set of variables. Translating customer data into a customer scoring, the segmentation model builds clusters of customers with homogeneous profiles, that can later be addressed with cluster-specific marketing and sales measures.
Customer segmentation variables: The characteristics of customers that are used to cluster them into homogeneous groups are called segmentation variables. Depending on the goal and type of the segmentation, variables can describe either geographic, firmographic, behavioral, or need-based characteristics.
Data pool: A data pool is a central repository of data where different parties within or across organizations can obtain, maintain, and exchange information. Data pooling describes the process of merging data sets from different sources into a single data pool.
Descriptive analytics: Descriptive analyses are used to describe and summarize historical and present data sets. Providing insights into what has happened in the past, descriptive analytics are often deployed as a precursor to diagnostic or predictive analytics, which attempt to explain why it happened or predict what will happen in the future.
Diagnostic analytics: With the help of diagnostic analyses, it is possible to clarify causes and effects as well as identify correlations and patterns between variables. Companies opt for this method of data analysis to gain deeper insights into a particular problem, for instance when examining market demand or explaining customer behavior.
ERP systems: An enterprise resource planning system, or ERP system for short, is used to provide cross-functional support for all the business processes running in a company. It integrates a variety of business applications and operational data that are processed and stored in a central database.
Gatekeeper: Controlling the flow of information into and within the buying center by actively filtering and selecting information that is forwarded, the gatekeeper has a crucial role in the buying center. Even though the gatekeeper’s involvement in the buying process is indirect, their influence on the purchase decision is significant. Common gatekeepers are secretaries or assistants.
Minimum viable product: In agile development, a minimum viable product (MVP) is an instrument for minimizing risk during the development of products, services, or business models. It is product created with limited efforts, but with enough features to validate and improve a product idea through early user feedback.
Predictive analytics: Predictive analyses use statistical modelling and machine learning techniques to predict future trends and events based on historical data. By predicting potential scenarios of the future, this type of analysis enables strategic decisions, for instance through predicting customer demand at different price points.
Prescriptive analytics: Prescriptive analyses deal with the question of how different actions affect a result and what is the optimal course of action in a given situations. Even though prescriptive algorithms open up the possibility of automated decision making through data-informed recommendations, they cannot fully replace human discernment as of today.
Social listening: Social listening refers to the targeted observation, extraction, and analysis of company, brand, and product references, as well as relevant terms on social media platforms, rating portals, blogs or forums. By analyzing social media sentiments, companies can generate insights used to guide strategies and actions.

Data-driven Sales

Algorithm: A set of rules or instructions designed to solve a specific problem or perform a specific task, often used in computer programming or data analysis.
ARIMA: Autoregressive Integrated Moving Average, a statistical model used to analyze and forecast time series data.
Churn Rate: The rate at which customers or subscribers stop using a product or service, often expressed as a percentage, indicating customer attrition or churn.
Cluster Analysis: A statistical technique used to classify data points into groups based on their similarities or dissimilarities, often used for customer segmentation.
Correlation: A statistical measure that quantifies the relationship between two variables, indicating the degree to which they are linearly related.
Cross-selling: A sales technique that offers customers additional or complementary products or services based on their existing purchases and demographics.
Customer Lifetime Value: A metric that represents the total value a customer is expected to generate for a company over the life of the relationship.
Data Cleansing: The process of identifying and correcting or removing errors, inconsistencies, or inaccuracies in data sets to ensure data quality and reliability.
Data Transformation: The process of converting or manipulating raw data into a more suitable format or structure for analysis, often involving data aggregation or normalization.
Descriptive Analytics: The branch of analytics that focuses on summarizing and describing the characteristics of a data set without establishing cause-and-effect relationships.
Diagnostic Analytics: The branch of analytics that aims to determine the causes or reasons for certain results or patterns observed in data.
Dummy Variable: A binary variable used in statistical models to represent different levels of a categorical variable, with a value of 1 indicating presence and 0 indicating absence.
Ensemble Method: A machine learning technique that combines predictions from multiple models to improve overall prediction accuracy and robustness.
Exponential Smoothing: A time series forecasting method that assigns exponentially decreasing weights to past observations, with more weight given to recent data points.
Forecast Accuracy: A measure that evaluates the accuracy of a forecast by comparing predicted values to actual values, often calculated using MAE or RMSE.
K-means: A clustering algorithm that divides data points into a specified number of clusters based on their proximity, with the goal of minimizing the intra-cluster sum of squares.
Linear Regression: A statistical technique that models the relationship between a dependent variable and one or more independent variables, assuming a linear relationship.
Machine Learning: The development of algorithms and models that enable computer systems to learn from data and make predictions or decisions without being explicitly programmed.
Net Promoter Score: A metric used to measure customer satisfaction and loyalty by asking customers how likely they are to recommend a product, service, or brand to others.
Neural Networks: A type of machine learning model inspired by the neural structure of the human brain, that processes and transmits information to make predictions or classifications.
Normal Distribution: A probability distribution that is symmetric and bell-shaped, often used in statistical analysis and modeling due to its prevalence in natural phenomena.
Normalization: The process of scaling or transforming data to a common scale or range, typically between 0 and 1, to facilitate comparisons.
Outlier: An observation or data point that deviates significantly from the overall pattern or trend of a data set, often requiring further investigation.
Overfitting: A situation in machine learning in which a model becomes too specialized to the training data and loses its ability to generalize to new, unseen data.
PivotTable: A data summarization tool in Excel that allows users to quickly and interactively summarize and analyze large data sets through grouping and aggregation.
Predictive Analytics: The use of statistical models and machine learning algorithms to analyze historical data and make predictions or forecasts about future events or outcomes.
Prescriptive Analytics: An advanced form of analytics that combines historical data, predictive models, and optimization techniques to identify the best course of action to achieve specific outcomes.
Primary Data: Data collected firsthand by a researcher or organization specifically for a particular analysis purpose, often through surveys, interviews, or experiments.
Regression: A statistical technique that models the relationship between a dependent variable and one or more independent variables.
Reliability: Assesses the extent to which a measurement produces consistent results under similar conditions, indicating the absence of random error or variation in the data.
Sales Cycle: The series of stages or steps involved in the process of selling a product or service, from prospecting and lead generation to closing the sale and post-sale activities.
Sales Dashboard: A visual representation or display of key sales metrics that provides an at-a-glance view of sales activities, trends, and performance.
Sales Forecast: An estimate or prediction of future sales revenue or performance that helps companies plan, budget, and make decisions.
Sample: A subset of data points selected from a larger population used to gain insights, draw conclusions, or perform statistical analysis on the population as a whole.
Scatterplot: A graphical representation of data points on a coordinate system in which each point represents the values of two variables, allowing the examination of their relationships.
Seasonality: A pattern or trend that repeats or occurs at regular intervals within a time series of data, often associated with recurring factors such as seasons or other temporal cycles.
Secondary Data: Data collected by someone other than the user or for a purpose other than the current analysis, often obtained from third party databases, reports, or sources.
Segmentation: The process of dividing a larger customer base into distinct subgroups based on common characteristics, behaviors, or preferences.
Sentiment Analysis: The use of natural language processing and text analysis techniques to identify and evaluate the sentiment, emotion, or opinion expressed in textual data.
Significance Level: The range of values that describes the uncertainty surrounding an estimate, helping to determine whether a relationship or difference is statistically significant.
Silhouette Coefficient: A measure of how well each data point fits into its assigned cluster in cluster analysis, ranging from -1 to +1, with higher values indicating more distinct clusters.
Test Data: Data used to evaluate or assess the performance and accuracy of a predictive model or algorithm, typically separate from the training data.
Time Series Analysis: The statistical analysis of data collected at regular intervals over time to identify patterns, trends, or make predictions.
Training Data: Data used to train or build a predictive model or machine learning algorithm, typically separate from the test data.
Upselling: A sales technique or strategy that offers customers a higher-priced or upgraded product or service than the one they originally intended to purchase.
Validity: Refers to the degree to which a test, scale, or instrument accurately measures or assesses what it is intended to measure.

Digital Lead Generation

A/B Testing: An experiment that compares two versions (A and B) of a web page or campaign to determine which is better at achieving a specific goal, usually based on user behavior or engagement metrics.
Call-to-Action (CTA): An invitation to take a desired action, such as clicking a button, registering, or making a purchase.
Capture Form: A form on a website or landing page designed to collect visitor information, typically including name, email, and other relevant details.
Click-Through Rate (CTR): The percentage of users who click on a specific link or call-to-action compared to the total number of users who viewed the content.
Content Seeding: The process of strategically distributing content across multiple platforms to maximize its reach and engagement potential.
Conversion Rate: Percentage of users who complete a desired action, such as purchase or registration, out of the total number of users who engaged with a campaign.
Earned Channels: Marketing channels where awareness and exposure are gained organically, such as through word-of-mouth, social media shares, or press coverage.
Engagement Rate: A metric that measures the level of interaction and involvement users have with content or a brand, often calculated based on likes, shares, comments, and other interactions.
Gain Creators: Elements of a product or service that contribute to its value proposition by fulfilling customer needs or wants.
General Data Protection Regulation (GDPR): European Union regulation that governs the collection, processing, and storage of personal data and aims to protect the privacy and rights of individuals.
Impressions: The number of times a piece of content or advertisement is displayed to users, regardless of whether it is clicked or interacted with.
Landing Page: A web page specifically designed to receive traffic from a marketing or advertising campaign, often optimized to encourage a specific action or conversion.
Lead: A potential customer who has shown interest in a product or service by providing contact information or engaging with marketing content.
Lead Magnet: An incentive offered to prospects in exchange for their contact information, such as a free e-book, webinar, or discount.
Lead Nurturing: The process of building relationships with leads through targeted communications and content, with the goal of moving them through the sales funnel.
Lead Qualification: The process of determining a prospect’s readiness to make a purchase, usually based on a lead scoring framework.
Lead Scoring: A framework that ranks and prioritizes leads by assigning numerical values to their likelihood of converting into customers, typically using criteria such as fit and engagement level.
Pain Reliever: Special features or solutions offered by a product or service to alleviate specific challenges or problems faced by customers.
Personas: Fictional representations of ideal customers based on demographics, needs, and behaviors, used to tailor marketing strategies and content.
Retargeting: An advertising strategy that targets users who have previously visited a website or interacted with a brand, with the goal of re-engaging them and driving conversions.
Sales Funnel: A visual representation of the customer journey, illustrating the stages from initial awareness to conversion.
White Paper: In-depth report or guide that provides valuable information or insight on a specific topic, often used for thought leadership and lead generation campaigns.

Negotiation tactics

BATNA – The “Best Alternative to a Negotiated Agreement” is the best option a negotiating party has if an agreement cannot be reached with the other side.
Calibrated questions – Questions designed to elicit specific information from the other party to strengthen the negotiating position.
Choice mindset – A mindset that encourages negotiators to find creative solutions rather than simply choosing between predetermined options.
Confrontational strategy – An aggressive tactic in which one party uses its power to strengthen its position and assert targeted interests.
Customer objection – An objection raised by a customer to a vendor’s or supplier’s offer during a negotiation.
Distributive negotiation – A negotiation situation in which both parties try to get the maximum benefit for themselves from a fixed amount of resources.
E-procurement – The process of procuring goods or services via the Internet or web-based applications.
Gain creator – Describes how products and services deliver relevant results and benefits to customers.
GDPR – The General Data Protection Regulation is an EU regulation on the protection of personal data.
Harvard model – An approach to negotiation in which the parties work out a win-win solution based on their interests and needs.
Integrative negotiation – The exchange of mutual concessions to create new value and a win-win solution for both parties.
Labeling – A tactic in which negotiators openly address and acknowledge the perceived emotions of their counterparts in order to build trust.
Lead negotiator – The person who leads a negotiation and represents the negotiating party to the other side.
Mirroring – A tactic in which one party in a negotiation mirrors the body language or tone of voice of the other party in order to build rapport and trust.
Negotiation database – A database that contains information about past negotiations to better prepare for future negotiations.
Negotiation playbook – A collection of strategies and tactics that a negotiating party can use to achieve a successful outcome.
Negotiation preparation – The analysis of the interests and goals of the negotiating parties and the establishment of the organizational setting.
Negotiation strategy – A predetermined course of action taken by a negotiating party to achieve its interests and objectives.
Negotiation tactics – The specific actions that negotiating parties take in individual situations to strengthen their position and achieve their goals.
Pain reliever – Describes how products and services solve specific customer problems and reduce difficulties, barriers, and risks.
Pie of resources – The amount of resources or benefits to be divided between the two parties in a negotiation.
Price negotiation – The individual bargaining of a price for a product or service in a negotiation between two parties.
Problem solving strategy – A strategy in which negotiating parties actively work together to investigate and solve a common problem.
Settlement range – The amount of flexibility a negotiating party has to achieve the desired outcome in a negotiation.
Similarity principle – A negotiation principle that emphasizes the similarities between the parties to strengthen the relationship and facilitate agreement.
Small steps strategy – A tactic in which negotiators make a series of small concessions to reach an agreement.
Social proof – The use of case studies and testimonials from other customers to substantiate a value proposition.
Supplier management – The process of selecting, evaluating, and managing suppliers and supplier relationships.
Target price realization – Compares the price achieved in the negotiation to a party’s target price set during preparation.
Time to close – Measures the average amount of time that elapses between the initial customer contact and the signing of a contract.
Ultimatum – A tactic in which a negotiating party sets a deadline and threatens to reject an agreement or walk away if it is not met.
USP – The “unique selling proposition” of a product or service that distinguishes it from the competition.
Value proposition – The summary of the specific benefits of a product or service to a customer.
Value proposition canvas – A tool for defining and optimizing the value proposition of a product or service.
Walkaway price – The price at which a negotiating party is willing to walk away from a negotiation.
ZOPA – The “Zone of Possible Agreement” describes the area in which an agreement can be reached between the two negotiating parties.

Price Strategy

Bundle pricing: In a bundle pricing strategy, companies offer (or “bundle”) two or more complementary products or services together and sell them at one price. This price is typically lower than the price of the individual components.
Costs of goods sold: COGS are the costs that are directly attributable to goods produced by a company that have now been sold. In addition to production costs, COGs include the costs to serve a customer.
Conjoint analysis: A conjoint analysis is a multivariate analysis used to determine customer benefit and willingness to pay. During a special type of survey, companies ask customers to rank separate product features or components in order to determine their preferences and to enable utility-based prices.
Contribution margin: The contribution margin is the difference between the price of a product and the variable costs connected to its production and sales process. The contribution margin can help determine the selling price range of a product and the profit levels that can be expected from the sales.
Cost-plus pricing: Under a cost-plus pricing strategy, companies charge a mark-up on the manufacturing costs of their products and services. Depending on how much profit they want to achieve, companies add a fixed margin on top of their variable unit costs.
Competitive pricing: A competitive pricing strategy focuses on prevailing market prices. This means that instead of using the costs of products or customer demand, the prices of competitors are used as benchmark.
Discounts: A discount is a reduction in price from a standardized offer or a list price. While on-invoice discounts such as volume discounts are captured in the invoice price, off-invoice discounts such as discounts for timely payments are not included in the invoice.
Dynamic pricing: Dynamic pricing uses intelligent algorithms and price bots that automatically collect data and adjust prices to reflect the current market situation and customer willingness to pay at the moment of purchase.
Freemium pricing: In freemium pricing, a combination of the words “free” and “premium,” companies offer a free basic version of their product with the hope that users will later pay for access to additional features and benefits.
List price: The list price is typically the reference price shown in official price catalogues or lists. The official list price is different from the price paid by a customer as it is transformed through different on and off-invoice discounts along the price waterfall.
Penetration pricing: Penetration pricing involves offering products at extremely low prices when they are launched in the market in order to create strong purchase and volume incentives. As sales increase, companies often improve their contribution margin per unit to such an extent that the high initial investment eventually pays off.
Price controlling:Price controlling describes the management of the end-to-end price process. Price control systems collect and analyze pricing data to monitor the implementation of prices. Through the use of special KPIs, deviations in performance can be tracked and corrective measures initiated.
Price differentiation: Price differentiation aims at maximizing willingness to pay through selling identical products to different market or customer segments at different prices. The most important types of price discrimination are spatial, temporal, personnel, and functional differentiation.
Price enforcement: Not all set prices are realized. Price realization or price enforcement is the improvement of price discipline aimed towards a reduction of uncontrolled off-invoice discounts and a uniform implementation of price models and rules.
Price setting: Price setting generally describes the process of defining a list price and standard discounts for products and services. The price setting process occurs on three distinct levels: Industry-level, product-level, and transaction level.
Pricing strategy: Pricing strategies refer to the processes and methodologies businesses use to set prices for their products and services. Common pricing strategies include value-based pricing, skimming pricing, and bundle pricing.
Price waterfall: A price waterfall is a tool to visualize hidden costs and expenses that impact the realization of prices. The visualization shows how list prices are transformed through various types of margin reductions into net prices that are charged to customers.
Skimming pricing: In a skimming strategy, products or services are introduced to market at the highest possible prices and then lowered as the product lifecycle progresses. This strategy allows companies to pass on high start-up costs and cost advantages in the later stages of the lifecycle to their customers.
Value-based pricing: Under a value-based pricing strategy, the prices for products or services are based on the perceived customer benefit rather than on costs incurred or a profit mark-up. When implemented successfully, a value-based pricing strategy can help companies to better exploit the willingness to pay of individual customer segments.
Willingness to pay: Willingness to pay is the maximum price a customer is willing to pay for a product or a service. This price reflects the perceived customer benefit and can vary significantly from customer to customer.