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10 Common Marketing Budgeting Mistakes and How to Fix Them
Compare Top AI-based Modeling Tools for Marketing Budget Management and Planning
How many new customers will we get if we spend this much on advertising? How much do we need to invest in media next year to achieve the sales target? Which communication channels really contribute to business KPIs and which ones only waste our money? If you have to deal with these questions on a regular basis, you will be interested in a tool that can answer all of them.
This information will be useful to marketers, investors, CFOs and CMOs of large companies that allocate at least $ 0.5 mln. on marketing. If you are trying to navigate through various tools for marketing budget management, the following information will give you a comprehensive analysis of the best solutions present on the global market today. We included all crucial details in the comparison, like technical characteristics, global capabilities, industry experience, price, etc. You can see a detailed comparison in the table below.
As you probably know, after the phase-out of third-party cookies, MTA became practically useless, so we are only considering the tools that are not affected by this change and continue demonstrating accurate evaluation in the new reality. Marketing mix modeling becomes an obvious choice in the current situation. Leading global companies like Apple, Coca-Cola, Facebook, Uber, etc. have been successfully using it to make data-driven decisions on marketing investments, maximize return on ad spends and minimize negative impact of crises. We are only looking into AI-based MMM solutions, since they are much easier to operate: you don’t have to be an expert in analytics, statistics and models building to implement them in your work, you also don’t need to hire teams of experts. All you need to do is upload all the necessary data from your CRM, agency, etc. and get models and the analytics on your marketing campaigns at the touch of a button. Models can be used not only for a retrospective analysis of marketing performance, but also to plan optimal budget allocation for your future campaigns based on historical data. By using models you can analyze your marketing mix with both online and offline communication channels and find out which channels contribute the most to your target KPI and which are not efficient enough.
Even start-ups without any history of ad placement can benefit from marketing mix modeling by using it for planning. If measurement and planning processes are properly organized from the start, it will be much easier to define a path to profitability and raise funds. Startups can take advantage of a new CheckMedia service that uses MMM (Marketing Mix Modeling) and market benchmarks to help validate your go-to-market strategy. By answering just a few questions, you can determine whether you have enough marketing budget to execute your strategy.
Shareholders and especially investors have shifted their focus from the company’s growth rate to its profitability, which means start ups no longer can simply pour money into advertising waiting for profits. Instead they should make the most of the available budget and make data-driven decisions on investments.
You can choose the most suitable solution depending on what tasks you want to manage, where your company operates, how much data you have, required optimization scenarios, preferred operational process and other important factors.
Comparison table
AdoptoMedia | Sellforte | Marketing Evolution | Why this option? | |
General | ||||
Managing tasks | ||||
Managing CAC | + | + | + | To evaluate the cost of attracting new customers |
Managing ROAS / ROI | + | + | + | To evaluate the return on your marketing budget |
Sales Forecast based on historical data | + | - | - | To plan and optimize marketing budgets on existing markets |
Sales Forecast based on benchmarking | + | - | + | To plan marketing budgets when entering new markets |
Brand awareness forecasts | + | - | - | To forecast brand awareness level. It is used in merchandising deals |
Media Mix Optimization | + | - | + | To optimize marketing budget for various criteria |
Developing path to profitability | + | - | - | To have ready-made strategies based on media mix optimisation for company profitability management, including exponential budget decrease / increase |
Users | ||||
Agency | + | + | - | Agency tasks - sell ad media with high AVBs and satisfy their client |
Marketing team | + | + | + | Operational management of marketing budget |
Executives | + | - | - | Operational business management |
Board Members | + | - | - | To return the money invested in marketing through the growth of the company's capitalization / profit |
Investors | + | - | - | To return the money invested in marketing through the growth of the company's capitalization / profit |
Industry cases | ||||
Bank | + | - | + | |
Crypto | + | - | - | |
Gaming | + | - | - | |
FMCG | + | + | + | |
Retail | + | + | + | |
Pharma | + | - | - | |
E-com | + | - | - | |
Automotive | + | - | + | |
Insurance | + | - | - | |
Real estate | + | - | - | |
B2b | + | - | - | |
Statrups / Fast Growing companies | + | - | - | |
Media & Enetrtainment | + | - | - | |
Global capabilities | ||||
USA | + | - | + | |
Europe | + | + | - | |
World | + | - | - | |
AdoptoMedia | Sellforte | Marketing Evolution | Why this option? | |
MMM capabilities | ||||
Data processing | ||||
Data processing standards | + | - | + | Data processing standards, such as MRC Outcomes and Data Quality Standards, are necessary to control the quality of transmitted data and ensure the quality of modeling results |
XLS import | + | + | + | Data upload through XLS |
ETL import | + | + | - | Data upload via integration with ETL systems, such as Oracle Data Integrator, IBM DataStage, SAS Data Management, etc. |
Predefined data connectors | - | - | + | Predefined connectors to industry data are needed to upload additional data for modeling for a given country. Connectors are usually made for each country, so it is difficult to use them for global brands |
Compliance marketing with financial data | + | - | - | Unification and synchronization of marketing invoice data with advertising campaign data allows you to additionally validate data for modeling |
Verifying data anomalies and logic check algorithms | + | - | + | Algorithms that allow processing uploaded data for typical errors |
Minimum data points for model building | 54 weeks | 162 weeks | 162 weeks | Amount of historical data necessary to build a model. In case no data is available, benchmark-based approach is used |
Training / test dataset | + | - | - | |
Model development | ||||
Methodology | + | - | + | A described methodology that includes the process of model selection by AI algorithms and finished model validation with a list of statistical tests makes the use of MMM auditable |
Statistical basis | + | - | - | Using statistical tests ensures the accuracy of KPI forecast (new customers, sales, etc.) for short- and long-term periods |
Third party independent audit | + | - | - | Models should be available for third-party audit. This allows organizing independent model validation at the company level |
1-button model builder | + | + | + | Building a model at the touch of a button with standard settings is for those who are not experts in MMM |
Professional interface with changeable AI settings | + | - | - | Possibility to select a model of a certain class according to MMM experts' settings |
External (existing) model import | + | - | - | Uploading an existing model and performing optimization on its basis |
Model export | + | - | - | Downloading a model as an XLS file allows using the model for calculations outside the system, in particular, use it as a part of company's P&L |
S-shape (response curves) features | + | + | + | Using response curves to take into account non-linear effects of advertising |
Auto-seasonality feature | + | - | - | Algorithm for seasonality adjustments allows cleaning KPI from seasonal effects. |
Avoid multicollinearity capabilities | + | - | - | This algorithm allows including in the model factors that are highly correlated with each other. This option is needed to take into account digital advertising of different formats |
Metamodeling | + | - | - | This algorithm allows building models without historical data based on a brief and model catalogue |
Brand awareness modeling | + | - | + | This algorithm can forecast brand awareness level depending on media mix. It is used at the product launch phase as well as by established brands for merchandising tasks |
Halo effects modeling | + | - | + | To take into account the mutual influence across channels (influence of TV advertising on performance advertising) or the influence of advertising for one product on another product |
Ongoing model's validation and adjustment | + | - | - | System for monitoring model quality when adding actual data and rebuilding a model, taking into account comparability with previous versions |
Optimization | ||||
Yearly | + | - | + | Annual budget optimization. As a result, client receives ad distribution across channels |
Calendar / campaign based | + | - | + | Budget optimization taking into account time frames of ad campaigns |
KPI based optimization | + | - | + | Media budget optimization according to the target KPI |
Budget based optimization | + | - | + | Sales volume optimization for a given budget |
What-if Scenario modeling | + | - | + | Modeling and comparison of various budget scenarios |
Reporting | ||||
Predefined dashboards | + | + | + | Standard dashboards within the system |
BI-integration | + | - | - | Export of modeling results to existing BI systems (Tableau, Power BI, etc.) |
AdoptoMedia | Sellforte | Marketing Evolution | Why this option? | |
Implementation | ||||
Operational process | ||||
End-to-end process for managing media budgets | + | - | + | A described process of applying models for marketing budget management and its implementation within the soft |
SAAS | + | + | - | Delivery as a cloud solution |
On-Premise | + | - | + | Solution is deployed on the client's infrastructure |
Project timing | ||||
First results | 7 days | 14 days | 3 month | |
Ongoing optimization | 6 month | - | 2 year |
All the information in the table is compiled from open sources and official websites of the companies. If you don’t agree with anything or would like to add some information, feel free to contact us.