Enhance customer relationships and help identify significant revenue / profit opportunities.

There are two sides to Marketing: growing relationships and deepening relationships.

Build brand.

Strategy: Know your customer Personalize with intelligence Engage across the entire customer journey Improve customer experience grown and deepen relationships

Increase efficiency: develop top down framework for customer engagment.

“You have to spend money to make money” adage is never been truer than in Marketing. Smarter and clearer about how you’re spending your dollars in support of your business.

Effectiveness: how do we get more out of everything that we do in Marketing?

Ultimately you have to grow the top line, you have to grow revenues in order to succeed. (Mix Quantic Accounting to Marketing).

Greater levels of integrity on the insights.

Two pillars: Drive financial efficiency and improve marketing effectiveness.

Drive financial efficiency: accountability to the business + provide greater transparency of investments.

effectiveness: plan campaigns with data and insights at key points of the marketing cycle.

What techniques provide Marketing the ability to adapt quickly to emerging information?

Bet on transparency

What are the right levers?

Agile is a collective concept that includes different techniques that provide the ability to adapt quickly to new conditions

One of the What tools does Marketing pivot and optimize towards its outcomes?

Agile tracks via EBM

Reaching strategic goals requires experimenting, inspecting, and adapting

The top two marketing challenges I have consistently encountered across various industries and companies are as follows:

• Find ways to bring incremental revenues beyond seasonality and cannibalism.
• Marketing’s biggest C-suite communication challenge is to accurately prove how effective marketing strategies are on financial outcomes. This struggle ranges from fact-based past performance assessments just as much as empirically deciding whether to decrease or increase Marketing Budgets, or even, at a more tactical level, which future marketing investments will return the greater pay off.
• Collecting the right data, making sense of complex and varied data, adding to the data.

The most important equation in Marketing is arguably ‘Return On Marketing Investment’ (ROMI).

Credit for picture

Beyond cost control and profitability decision making, adopting a financial measure like outlook sharpens the focus on business goals. It is typically calculated by doing a baseline-lift valuation on short-term sales, where the effect of a marketing effort on sales is separated from the level of sales that would have been reached without the marketing effort. By comparing the returns and costs of marketing, ROMI encourages transparency and builds trust as financial impact is a language that top management understands and evaluates against. ROMI helps compare marketing decisions by revealing the ones with the higher efficiency.

Let’s break the ROMI equation down:

ROMI = Incremental margin − Marketing investment / Marketing investment

The incremental margin is of course a critical measurement as without it, we can’t calculate returns. Consider this simplistic example:

Then the incremental response is 2400 = (0.6% - 0.12%) * 500,000..

.. and Marketing should take credit for 80% for the 3000 influenced responders (2400/3000)

The measure enables the comparison of efficiencies between different marketing investments. It also allows for experiments and guides the business on marketing budget allocation to best maximise sales.

Measure and optimize the strategy across all channels:

MMM sets campaign budgets for each media channel - dictating both the overall spend allocation for the campaign and the proportional spend across each channel.

How much should we spend? Where should we invest? What’s the impact?

Incremental / absolute lift.

ROMI-managed companies use marketing mix models, or when media is involved, media mix modelling, as a critically important top down technique to move beyond budget the adjustment decision-making process to compare the high level incremental impact of a range of marketing efforts on sales over time across digital and offline channels. This allows moving beyond measurement to strategic planning to estimate top line future opportunities of potential outcomes performing “what-if scenarios”, evaluate quickly and select the optimal marketing mix amongst the alternatives that most likely to pay off. MMMM tools can be productive as a means by which users enrich their judgmental processes by adding to their learning.

Data used to fit marketing mix models. The response data needs to be at the same level of granularity as the ads spend data.

media spend, response data (sales), channel data, number of views, clicks, and product price, promotion, distribution, and control variables, such as weather, economic conditions, seasonality, and market competition

Past performance may not be the best indicator for future performance. Conventional MMM only provides an estimate of the past performance but does not specifically attempt to estimate what the performance will be in the future. Customer behaviour and market conditions may change in the future and affect marketing performance. Thus, the results from MMM should be used with caution when making decisions. MMM is often criticized for its “rear-view mirror” or after the fact perspective of marketing mix impact.

However, new simulation models can provide scenarios for managers to assess future potential results. To aid in evaluating new products, they have begun Monte Carlo simulations integrating the degrees of uncertainty and drivers of a project. The simulations enable the marketing team to assess the range of potential outcomes and to apply market models and to assess discounted cash flow. The analysis allows the understanding of likely outcomes to gain a degree of confidence of the amount of risk.

Measure and Optimize the journey Tactically within addressable channels with Multi-Touch Attribution

Tactical decision making.

Relative lift.

How should we allocate media within a channel? Who should we target? Where and how should we reach them? How often should I message them?

MTA optimizes budgets, it’s a technique that gives intra-channel optimal plan recommendation based on MMM budget constraints. This ensures the activations are optimized for each specific channel.

Media performance: What addressable marketing efforts drive the highest incremental sales? What were the top performing publishers by media type? How have last week’s campaigns been performing?

Forward looking optimizations: How should we allocate next week’s media plan to maximise sales? How can we shift gears this week to improve the performance of a given campaign? What is the impact on sales if we change the media mix? Budget? Cost per goals?

Frequency analysis: What is the optimal frequency cap by media and by publisher? How many times do our customers see an ad before they convert? How efficient are our digital ad campaigns?

Customer journey analysis: What are the most common paths to purchase? How do different audience segments perform aginast addressable media channels? How long does it typically take for consumers to convert following a media exposure?

MTA optimizes in flight. MTA attribution is used to track results of campaigns as they run. It assesses performance across the most granular dimensions of media. Intra-channel optimizations can be done based on near real-time results. Cross channel shifts can be evaluated periodically throughout campaigns.

Multi-touch attribution (MTA), on the other hand, is a solution that offers tactical in-flight insights by determining the relative contribution of individual campaign impressions towards a goal for the purpose of performance measurement and optimizations. It suggests ways to optimize short-term marketing performance. It focuses on addressable channels and leverages granular, user-level data to analyze performance in near real time. It does this by calculating and assigning fractional KPI credit to the marketing touchpoints and dimensions (publisher, placement, creative, offer, etc.) along the consumer journey that influenced an action (e.g. a sale) towards the desired outcome of the campaign. Marketers can use this insight to make smarter tactical decisions, such as which call to action to use or which keywords to bid on.

A fundamental problem in measuring advertising effectiveness is to quantify how revenue should be attributed to multiple touch-points along consumers’ conversion paths, which is the sequence, timing, and engagement in advertising channels along the purchase funnel.

By assembling information about user characteristics, media touch points, and sales/conversion data, marketers can understand which combination of channels, audience targets, publishers, devices, creatives, search keywords, or other marketing considerations are performing most effectively against their Key Performance Indicator (KPI). Thus, they are widely regarded by practitioners as a proxy for optimizing campaign performance. Contrary to media mix modeling, it is a bottom-up measurement approach that requires individual-level data.

An individual’s consumer’s decision to purchase has four distinct drivers: *Purchase propensity (predisposition to purchase) *Traditional media *Non marketing drivers (seasonality, discounts, economy) *Digital media

MTA only captures the digital media effects dimension.

Optimize all marketing investments, holistically. Achieve Better Results by Combining Methods

Unified analytics combines the functionality of a market level, top down model (MMM) and an audience-level, bottom up model.

By combining both approaches, marketers can further corroborate which channels are contributing to the pre-defined KPIs while preventing misguided conclusions when gaps between these two methods arise. Blending the detailed view from MTA with the higher-level analysis provided by marketing mix modeling, companies gain more accurate measurements. However, the different data sources and levels of data capture make the automated reconciliation of the two approaches difficult.

Marketers’ need for an integrated view of their marketing performance is as critical as ever. While marketing mix modeling and multi-touch attribution have their distinct advantages, marketers can realize the highest returns when they are used in tandem. By bringing insights from both methods of analysis together, marketers can get the comprehensive view of performance they need to inform their next best action within and across channels.

For example, consider a brand that is running multiple campaigns across a number of online and offline channels. Using marketing mix modeling, the brand can analyze all the drivers of performance and determine how to best allocate its budget between channels on a quarterly or annual basis. Using multi-touch attribution, the brand can then drill down deeper and allocate channel budgets to the highest-performing publishers, placements, keywords, creatives, and other tactics while campaigns are still in flight. Armed with this strategic -and tactical-level insight, brands can make a broad array of decisions to maximize the efficiency and effectiveness of their entire marketing portfolios.

Most brands today rely on both online and offline channels to drives sales, revenue and other desired business outcomes. By leveraging a holistic measurement approach that reconciles data and insight from marketing mix modeling and multi-touch attribution, marketers can enjoy the truly comprehensive view they need to make the right decisions, at the right time, to optimize performance across every area of investment.