Market Simulations. A New Approach to Marketing Analytics. Simulate Your Market

Transcription

1 Market Simulations A New Approach to Marketing Analytics Simulate Your Market

2 TABLE OF CONTENTS THE CHANGING SITUATION... 3 THE SIMULATION CONCEPT... 4 HOW IT WORKS... 5 Variables and rules... 5 Initial Conditions... 6 Calibration Algorithms... 7 What-if scenario analysis... 8 SUMMARY... 10

3 THE CHANGING SITUATION With the proliferation of new media types, the explosion of available data, the rising influence of social networks, and a general desire to reduce advertising spend, marketers are finding it increasingly difficult to pick strategies that produce desired outcomes. As of July 2012, one out of every two U.S. marketers felt marketing technologies did not meet their needs. 1 Even though many technologies have emerged in the past few years, none are able to simultaneously: We believe that simulation is an approach that allows its users to achieve these goals. Our goal is not to displace today s approaches, but to extend the current analytics with better, broader, and more efficient solutions. 1 Forrester Consulting: The Key to Successful Cross-Channel Marketing Commissioned by ExactTarget, Oct 31, 2012

4 THE SIMULATION CONCEPT When pilots practice flying new airplanes, they use flight simulators. When doctors train, they use models of human bodies. When engineers design computer chips, they test their ideas in silico, before sending them to the factory. When marketers test ideas, strategies, and tactics about consumer markets, they use Concentric simulation software. Our applications recreate the dynamics of consumer markets with accuracy that matches the highest statistical standards of any existing media-based analytic tools and provide insights that go beyond what alternatives can deliver. Users of Concentric diagnose the performance of offline, online, and social marketing vehicles. They explore strategies to develop and launch new products and evaluate the risk of new competitive entrants. They forecast consideration, perceptions, word-of-mouth, sales, and return on investment for each of the brands competing in the market and for each of their target consumer segments. Finally, Simulation allows users to optimize the allocation of resources across product and marketing portfolios. Three key ideas define the benefits of Simulation: A more complete answer Currently marketing analytics are performed by separate teams and service providers, each working individually on parts of the analysis Effectiveness of advertising investments with marketing mix models Contribution of digital media with cross-channel attribution Brand performance with consumer research Measuring word of mouth with social tracking. Simulation provides a revenue maximizing and a risk minimizing approach for evaluating planning scenarios prior to program execution by forecasting their impact on sales, brand equity and ROI simultaneously. A team of empowered users As noted above, analytics are currently performed for marketers by internal teams or service providers without easy tools for collaboration or ideation. A cloud-based solution that improves the flow of data into a system providing fast distributed processing, and supporing easy story telling and visualization, will create a new type of user. Teams and individuals will become more agile in their decision making while providing the kind of accountability that is missing in many organizations today. Ad hoc questions and answers An engagement with a typical analytics provider can take anywhere from weeks to months to complete. Due to the automation achieved through software, simulations take minutes to update and re-calibrate with new information. Once a simulation is calibrated and ready to use, new investigations happen continuously and in real-time. Unlike consulting projects that come with defined project scopes, Concentric offers users the ability to run countless analyses: Simulation allows the user to war-game hypotheses in order to understand the best response to current market challenges.

5 HOW IT WORKS All Concentric software is built on a simulation technology called Agent-Based Modeling. The agent-based model replicates the macro-level behavior of markets (sales, perceptions, word-ofmouth volume and sentiment, and touchpoint effectiveness) by simulating the micro-level interactions among consumers and consumer exposure to outside influences like marketing and products. The components of our Agent-Based Model are: 1) Variables and Rules 2) Initial Conditions 3) Calibration Algorithms 4) What-if Scenario Analysis We will describe each in turn in the sections below. VARIABLES AND RULES Our algorithms start by describing the interactions of the key components (or agents) of the system with a few simple individual-level rules that lead to aggregate behavior, matching what we observe in reality. To begin, we describe consumers. Consumers have properties, including awareness and perceptions of different brands. These properties are the drivers that govern what is important to each consumer when making decisions. Consumers are also connected in a social network the fabric of a consumer market. Finally, consumers engage in behaviors related to products: they post online, purchase, and talk. A few rules define how consumer properties drive the behaviors. For example, the more aware consumers are about a product, the more likely they are to make a purchase. We use variables to change the impact of properties on behaviors. For example, the greater the social density, the more likely information will spread about the alternatives in the market. While behaviors are intentional, consumers are also affected by events, such as overhearing a friend talk about a new product or reading an online review. These events are likely to change awareness and perceptions. In addition to people in their social network, consumers are affected by outside factors, such as marketing, influencers, the category seasonality, or the product itself. These external factors create additional events that change the properties of consumers, and can be influenced by media investment and creative quality. So what we have now described is the entirety of the Concentric model. The diagram below shows all the variables, rules, and intervening factors. The most important point here is that unlike most data analytics approaches, which have dependent variables (like sales numbers) and independent variables (like marketing investment), an agent-based

6 model is a system dynamics model in which all variables are interdependent. This means that everything affects everything else. Sales are not a final outcome: the more people buy a product, the more people experience it, and the more people change or solidify their perceptions and awareness. Product/Offer Design Hear Word of mouth Social Influence Influencers Drivers Read Online Post Awareness Impact Awareness Awareness Decay Percep on Decay Post Online Percep ons Percep on Poten al Percep on Speed Ra onality Marke ng Investment Crea ve Quality Crea ve Emphasis Experience Ad Annual Reach Weekly Reach Experience Product Product Design Usage Speed Connec vity Usage Frequency Discussion Impact Social Density Talk Discussion Decay Purchase Category Seasonality INITIAL CONDITIONS All variables and rules of the above schema are informed through a diverse set of information and data that forms the initial conditions of the agent-based model: 1) Consumer research like brand trackers, focus groups, or panels, inform consumer properties 2) Media and sales data, which are usually used in any marketing effectiveness analysis 3) Information about the actual performance of the product, like product specs and industry reports 4) Social tracking information about the volume and content of conversations These disparate data sources, which were previously analyzed in isolation, are now integrated into initial conditions for Concentric simulations. There are two types of initial conditions:

7 On one hand we have inputs over time, like marketing investment (from a media plan), product changes which may occur during the year, category seasonality, and some market events. On the other hand we have settings that we are only interested in inputting at the first moment of the simulation, because we want to forecast their evolution over time. Here is the key to agent-based modeling: All that the technology does is combine the initial conditions with the rules of the market. The outcomes result from the logical evolution of the variables over time based on the interaction of these conditions and rules. CALIBRATION ALGORITHMS Users are interested in four key metrics: awareness, perceptions, sales, and word of mouth. The first thing to do when running Concentric is to make sure the simulation forecasts match the real world measures of these KPI s. To do so, the software compares the simulated results with the real data and measures the error between them. To improve the match between the simulation and the real world, a user identifies a set of initial conditions to vary. Perhaps these are chosen because the user did not have the best information or simply had no information at all. An automatic calibrator systematically adjusts parameters, runs Monte Carlo simulations, calculates the error margin between the updated simulation and the real results, and continuously narrows the search until it finds the variable settings or the rules that best fit the simulation to the observed real world results.

8 WHAT-IF SCENARIO ANALYSIS Once the user is satisfied with the validity of the diagnostics and the forecasting accuracy of the Simulation model, the user creates what-if scenarios. There are plenty of options to explore in Simulation. Users change the media budget for their own brand or a competitor s or explore various media mixes. They introduce new products or competitors into the market or change features of the product. They prepare for unanticipated PR or viral events. They change the nature of the consumer segments and anticipate tastes before they happen. All simulations in the Concentric software are probabilistic, which means that when a user re-runs the same scenario twice, you may get different results. So if you run a scenario three times, you may get three different sales outcomes. As the software runs more and more simulations, a process called Monte Carlo analysis, it forms a distribution of outcomes. This distribution is easily represented through a box plot, which shows the minimum and maximum of outcomes, the top and bottom 25%, the middle 50%, and a median outcome. The box plots help the user understand the confidence to have in Simulation

9 forecasts: the wider the box plot the lower the confidence of the baseline scenario, which is the scenario used to calibrate to past performance. Box-Plot The box plot also helps you compare scenarios. Adding a new scenario, called Messaging Shift we see that it performs better than the baseline, as the median outcome is higher. By showing the two scenarios side by side on four different metrics, the user can identify their trade-offs. Although the messaging shift scenario increased sales, it has a potential downside for awareness and word of mouth. The most useful part of Simulation is the comparison of multiple scenarios over multiple metrics there is no limit to the number of ideas and strategies can be tested and explored.

10 SUMMARY Simulation will transform marketing analytics. Concentric provides a system that combines social science and marketing science to solve specific marketing challenges and enhance executive processes. Simulation reinvigorates marketing innovation by empowering marketers to evaluate and optimize out side the box programs that they may have been uncomfortable executing in the real world before safely evaluating them in a virtual environment. What makes Simulation unique for solving challenges is that it can do all of the following simultaneously: Business Strategy Comparison Campaign/Channel Attribution Media Optimization Creative Content Optimization CRM Program Optimization Corporate Social Responsibility In-Store Strategy Pricing Analytics Product Development Product Launch Support Trade-dollar Assessments Targeted Media Buying Additional benefits of a simulation approach stem from the implementation of a unifying process to: Improve resource allocations Make real-time/near-time decisions Identify new markets Communicate insights Facilitate change Encourage collaboration Enhance transparency Accelerate the development of new products/services With a more complete answer, at lower costs, and at faster speeds, simulations are getting broad adoption. We hope you join Concentric on our quest for better marketing analytics.