Every performance marketing team conducts weekly business reviews to evaluate current performance, understand how the team is pacing against targets, identify areas needing attention, discuss ongoing tests, and take decisions.

What truly makes a weekly business review effective? How to make the most of your WBRs?

Over the last 6 years we explored the reality of WBRs at large scale-up and enterprise performance marketing teams - let’s dive deeper.

What does a great WBR look like

Outstanding weekly business reviews delve deep into performance and ongoing tests. Teams challenge existing hypotheses and analyze performance holistically. This requires all stakeholders involved to have appropriate context - ongoing tests and hypotheses, business effects (e.g., trends and seasonality), etc.

What is supporting all of this? Data. 

Great teams are able to:

1) Have a consistent view of all relevant metrics and a shared understand of their meaning

2) Monitor KPIs over time on dashboards

3) Monitor performance across key variables (e.g., geo, channel, etc)

4) Go deeper and test new hypothesis fast

5) Answer ad-hoc questions fast

Most scale-ups and enterprises teams have nailed #1 to #3. The problem lies in #4 and #5.

The challenges

Inability to go deeper, test new hypothesis and answer ad-hoc questions

Teams have access to dashboards that cover the high-level overview and the common breakdowns and splits. However, looking at data from new angles (e.g., cross-channel analysis, new breakdown or split, new target metric) or diagnosing performance changes is not straightforward. There are no “predefined” dashboards for this purpose. 

How do teams go about it? They either ask for data support or find workarounds (i.e., spreadsheets). The former often takes weeks or months, not being a viable option. The latter enables teams to move fast, but takes time, has many limitations (e.g., data volume size) and is error-prone. In practice, many hypotheses are not tested.

Manual data preparation

Many marketers still spend 3-5 hours every Monday preparing weekly business reviews. This often involves blending attribution with channel data on a granular level and pulling additional metrics or data from the ad platforms. Another use case is budgeting and pacing, which is often manually managed in spreadsheets. These manual processes are time-consuming, taking away from insights gathering and campaign optimization. In addition, spreadsheets often become complex, leading to manual errors. Recognizing this reality, Forbes recently described most of today’s marketers as  “data janitors” (read more here).

Bonus point: limited collaboration

Takeaways, insights and learnings are currently collected across slide decks and emails with limited context, as stakeholders don’t have direct access to the corresponding dashboards and reports. As a result, answering follow-up questions requires pulling the corresponding dashboard or report, changing filters, etc. Often, these questions cannot be answered because filters, access to granular data or visualizations are missing. Thus, it’s hard to go deeper, leading to slow iterations and some questions left unanswered.

The root-cause

Access to data is not democratized. Marketers have access to predefined dashboards that cover the high level overview, but are not sufficient to test new hypotheses (e.g., new data slices) and go deeper.

The outcome? Marketers can’t answer new questions quickly.

Many hypotheses are not even tested. Most ad-hoc questions are not even explored or answered too late. Manual analyses in spreadsheets are limited and error-prone. This all leads to missed optimization opportunities. As the digital marketing landscape evolves faster, this challenge hinders performance marketing teams’ ability to be agile and adapt quickly.

What if marketers could go from question to insight in minutes? That means testing every hypothesis or answering every ad hoc question in the meeting itself. 

This is the new way where marketers can iterate fast with data.

Let’s unpack this.

The new way - focus on insights and iterations

Achieving the ideal state - where marketers can dig deeper, quickly test new hypotheses, and answer ad hoc questions in minutes requires a shift in the way marketing teams work with data and collaborate.

No data preparation - Granular data automatically joined and refreshed

Marketers should focus on insights, hypotheses and tests. Not on data preparation. They should be curious to explore data and uncover insights. Without manual work or waiting for data support. This requires having attribution data automatically joined with channel data, down to the most granular level.

New question or hypothesis? Answers in minutes

Marketers should be curious to explore data and uncover insights and patterns. This requires:

1) All data in a single place (channel, analytics, budgets and targets) with all relevant metrics next to each other (e.g., Incrementality, ROAS, MTA). This way patterns and insights can be easily drawn, without switching between tabs and platforms (e.g., BI tool, ad platforms, spreadsheets, etc).

2) Flexibility - marketers need to be able to create and edit metrics, filters, dashboards, reports, etc. to slice and dice the data by any dimension (e.g., channel, campaign, product, brand). All of this within a governed environment to avoid misunderstandings about metrics or numbers not matching. This way they can answer any question in minutes, without having to wait for data support or manually exploring data in spreadsheets.

3) The ability to go from the big picture to the granular in just a few clicks (e.g., from a cross-channel overview to a channel deep dive and down to ad level) to diagnose performance and uncover opportunities fast. This way they can answer any question in minutes, without having to wait for data support or manually exploring data in spreadsheets.

Bonus point: Effective collaboration

Uncovering insights requires collaboration between marketers. Oftentimes also with other teams or partners (e.g., creative team, external agency). Bringing all insights, conclusions, hypotheses and decisions together in one place accelerates learning processes. Additionally, displaying them alongside evidence (e.g. dashboard) helps set the right context for answering follow-up questions (e.g. Why did we move $200k from channel A to B two weeks ago?).

The impact

The ability to quickly iterate with data allows marketing teams to uncover insights on the go and optimize performance quickly. For this, marketers need to “own” reporting. This is the only way to go from questions to insights in minutes.

This way marketers can make the most out of their WBRs, exploring live hypotheses, answering ad-hoc questions on the fly and collectively organizing learnings and takeaways.

Curious to learn how Delivery Hero, Preply and Unobravo go from questions to insights in minutes? Hear it from Filippo Gallignani (ex-VP Performance Marketing and CRM at Delivery Hero, ex-CMO at Preply, CMO at Unobravo)