How To Brief A Digital Analyst

Cut through the noise and get what you need

Through data you are trying to avoid the biases and problems that come with making gut decisions. However, it is important to get your briefs right to avoid unintentionally relying on an analyst's gut rather than clear insights.

Many people think data is only numbers but here it also refers to qualitative data, think customer surveys, reviews etc as that plays a big role in transforming your analytics function from graphs to insights. 

Develop good foundations

A data programme needs a good foundation. Without a Measurement Framework, data capture process and someone experienced in working with data trying to conduct analysis will take a long time with weak insights and low trust from the organisation. 

​

One key part of your foundation is the skills & experience of your analyst. Data may be made of simple ones & zeros but actionable, relevant, timely insights depend on context & experience. This means analysts will often specialise in one area or organisation. This may seem obvious but the assumption an analyst can interpret any data is pervasive & holds many companies back. Often you will find a large marketing team, management, creative & technical ecommerce teams and one analyst trying to make sense of it all. As we will discuss later your brief needs to give them a running start before they start heading in circles.

​

The second is the quality of your system and processes around how to collect, store, document, analyse, report and disseminate insights. Data affects almost every part of the business and changes rapidly as tools and business practises change. If a company is not maintaining their data the foundation will break down.

A good brief draws insights from your data to power business decisions

Building on your foundations

With well documented, reliable data and an experienced person ready to analyse it you can start to turn data into insights and optimisation.

Before we get into that, it is important to cover two things that stifle performance optimisation programmes.

​

The business must have a clear direction and be willing to adapt. Without a North Star to aim at the analyst will be forced to try and map the whole ocean. Without change there can be no magic in the data, any brand who thinks their market, customers and organisation should stay the same has no need of analytics, only status reports. These two things often lead to dissatisfaction with the insights programme and high analyst turnover.

​

With all this in place you can start to think about what you want from your analyst and normally this starts with a question. 

Types of questions

Analysts are not mind readers; the purpose of a brief is to establish what the analyst should be trying to achieve. Often people ask questions that have no real yardstick to measure by so get a response the analyst thinks they can support if questioned, which is raw data.

Examples of these types of questions are: how is my site doing, is our marketing effective, what happened last week? 

It is like a complete stranger saying, how did I do running across that field? The best you could do from a data perspective is tell them how fast they went as a rough guess.

If an analyst receives these types of questions, without explanation, context or an end goal  they’ll probably spend a lot of time pulling a lot of data in the hope that some of it sticks.

The Why & the How

If it is very early days, you can create a Customer Journey map & benchmarks but then you need to improve and that means you are  looking for the Why & How.

The Why is the insight into the finding. The How is the Recommendation.
Recommendations come in many forms but the main two are how to improve performance + what additional data is needed to form a recommendation. 

Remember, recommendations into how to improve performance are rarely as straightforward as the requestor hopes for. Analysts are not generally in a creative or performance role. They can generally only measure what is there. 

If one campaign is working well, the other badly, they can recommend shifting budget to the higher performing one. If there is only one underperforming campaign there is often no one, easily changed reason.
The best way to reduce this is to write down all the variables about a Campaign or launch. Then over time learn what variables have what impacts. Before this there is too little for an analyst to make recommendations with confidence.

The best way to work with an analyst is make them a part of a process. Try to establish the scientific method. Have an objective. Understand what you Know vs What you believe vs where you have no idea. Get information and hypotheses out of people's heads and into shared docs, make it accessible to everyone. Ask people to add to it, engage and debate it. 

Recommendations to get more data are often put to the bottom of the queue as action and getting the next campaign ready is prioritised. This limits the impact of insights. Websites and website pages have many moving parts to be tracked. AD campaigns have multiple channels and creatives. Always build and expand your foundation,  the best brief + analyst in world can’t magic insights from empty databases.

How to craft the brief

Below is a template you can use to ensure consistent briefs to your analyst. There are examples in red

Situation: Provide background and direction for the analysis

We are focused on growing our profits without requiring additional sales

Objective: Provide information about what is trying to be achieved. The more specific the better. Break large briefs down into smaller ones where necessary. Use Metrics & Dimensions where appropriate to help reduce guesswork.

Increase the Purchase Transaction Conversion Rates from Mobile Sessions Landing on our Homepage

Task: Frame the parameters and key areas of the analysis.

• What was  the impact of adding Pop Up on the 6th Feb. Last major update was on the 15th Jan (See linked Calendar for details of changes). 

• To understand what is having the biggest effects on performance from a Traffic source and New/ Return customer perspective

• Are there any obvious issues with the Conversion Rate

• If so, what?

• How confident are you and why?

Insight & Hypothesis: provide business insights and context to focus the analysis

• The Products we show on the page don’t entice our users because they are not relevant to the Ad that brought them there

• The Checkout Flow breaks on some Mobiles/ Browsers

• The page loads slower than average causing users to Bounce

• We recently shifted to a more aggressive Acquisition strategy and are maybe getting lower quality traffic

• We are thinking about changing the menu as we think users struggle to understand the groupings

• We cannot change the information required in the checkout or product pricing

• We have capacity to test Pop Up designs and Product pages. The category page design is fixed for the next two months, due to backlog bug fixes

Answer Format

• A number or feedback - Email (the conclusion)

• Trends, Dashboard,  excel / dashboard (numbers)

• Conclusions/ Recommendations backed by data, qualitative insights - Powerpoint

Please provide your recommendations in slide format with a one slide summary for sharing

Final thoughts

Create Benchmarks for current performance then targets to help you reach your objective. Create a log of what you are trying on your channels. Daily is best. It can be linked to the Marketing Calendar but should show all your acquisition, on site & CRM efforts. Even better if you can add market or competitor movements. If a competitor launches a splashy new discount campaign it is likely to affect you in ways that can be seen in the data but not easily explained. 

Get there and talk to people. Give your Analyst a real budget. Brand will often happily spend $100k on marketing a month but balk at $10k as part of the analytics budget. Being ‘data driven’ means giving it access & resources to make an impact not report on what happened.

Trying to get numerical data to explain the absence is often a futile exercise. Ask customers, prospects & the general marketplace will give you the reason your product or blog failed. Do this on repeat and you will start to get some great benchmarks and explanations around the charts and conversion rates you analyst trots out every meeting.

Get there and talk to people. Give your Analyst a real budget. Brand will often happily spend $100k on marketing a month but balk at $10k as part of the analytics budget. Being ‘data driven’ means giving it access & resources to make an impact not report on what happened.