Learning from the past can help you plan for the future. Rest assured I’ve got a bit of experience with this approach as my marketing forecasts have hit close to target on more than one occasion by applying it. However, the last 12 months and the upcoming year has and will continue to throw curve balls and make predicting performance harder, and whilst the past isn’t as reliable for forecasting future gains, it can still be pretty helpful to get your started.
Whatever you do, do it fairly swiftly
The defining word for the year ahead should be ‘agility’ – being willing, able and committed to making quick decisions, pivoting your approach or testing and learning as much as possible in order to keep up or hopefully stay ahead of consumer behaviour changes, demand and expectation.
To achieve this you definitely need quick data collection methods and ways of processing the information to make smart decisions fairly swiftly. Some methods I’ve used are definitely time consuming when stitching data sources together, so perhaps a first port of call is to review the platforms and processes to identify if any may slow down progress, and could be improved?
So in this time of uncertainty how can you plan your digital marketing activity?
Data by it’s very nature is typically in the past, it’s rooted in what’s already happened and even predictive analytics needs to look back in order to think forward. So, even in times of flux, past performance can certainly provide some benchmarks from which you can create marketing plans. Whilst many industries have been shocked to the core with a lack of demand or ability to deliver their service, and others have succeeded beyond recognition, there are still patterns in seasonality, business cycles, and demand that will remain similar no matter what is happening in the world.
The patterns may be skewed in strength or timing but they’ll still appear, so it’s wise to know what these may be from looking back at your data. Fortunately we now have a year’s worth of COVID impact data as well to overlay, to gauge just how much these patterns have shifted.
Business performance
At this level I recommend plotting changes over time in revenue, profitability, number of new customers/clients, sales, AOVs etc (whatever you can get your hands on) to determine peaks and troughs in performance. This can help with planning bursts of activity, or determining whether your marketing strategy should focus on filling the gaps or maximising the peak opportunities.
If you’re in travel, generating sales for the shoulder months is a constant headache, and this exercise helps to establish when the business really needs a marketing boost to generate demand.
This analysis can also be used to look ahead if sales in the future are yet to be fulfilled. For example if you have projects in the pipeline, or guests yet to go on holiday with you (but have booked in advance). Knowing your future capacity, and the gap between actual and target can really inform when campaigns need to be launched, when budgets need to be assigned, and possibly if promotional messages need to be activated.
Here is an example of how I’ve looked at business performance data to help with marketing decision making for a brand in the travel and tourism industry.
This graph is a little bit of a brain paralyser with all the colours and data points, but if approached methodically it offers some useful insight into the patterns of booking and holidaying behaviour vs. target capacity for the year ahead.
What this graph revealed to me was:
It was also adapted to filter by location, customer type and accommodation type to identify variances and inform marketing decision making on targeting and messaging.
Customer performance
Customer data can be analysed on a case by case basis, or more preferably in cohorts to understand propensity for repeat purchase behaviour, the profile of highest value customers etc. but also to help identify new segments and targeting opportunities.
Especially in the last 12 months perhaps you have a new customer profile that has organically grown but could be elevated to a new level if you actively communicated with these consumers. I’d definitely advise reviewing your customer profile, even if it’s to confirm that it hasn’t changed!
Direct to consumer brands (DTC) will likely have seen their customer data skyrocket as ecommerce has exploded, and there is a lot more information at their fingertips. Think about analysing your customer data based on lifetime value, one-off purchasers, repeat purchasers, and perhaps lapsed customers, and potentially creating lookalikes from the most lucrative segments, or honing in on the core groups with better targeted campaigns, products and/or services.
Marketing (but more specifically digital marketing) performance
Since I work for a digital agency I’m more qualified to offer advice on the aspects of tracking and measuring digital marketing activity, however I’m also a strong supporter of closing the loop between online and offline marketing wherever possible, as well as understanding the impact of offline marketing activity on online performance. But for planning your marketing activity, I’m staying firmly in the digital marketing camp when recommending how to plan for the year ahead in this article.
Discovering trends
Like business performance data it’s all about understanding trends and gathering as much historic marketing performance data as possible. This reduces the impact of anomalies and can make you appreciate how things may have changed (or not) overtime, perhaps without you even realising it.
When planning my clients’ digital marketing campaigns I jump straight to their website analytics platform. Usually this is Google Analytics. I take a look at patterns in traffic acquisition, device usage splits, location variances and landing pages, noticing % increases MoM and YoY as well as diving into why these changes may have occurred.
It takes a confident planner to appreciate whether stark changes in performance over time is as a result of a proactive decision or activity, or as a result of a macro trend (yes, something like COVID!). The confidence to determine whether the trend will continue if you do nothing (or continue doing what you’re doing) vs. steering an alternative course with a new strategy, approach or channel is what can set you apart and improve your chances of success.
Here are some examples of how I show my plans, taking the key variables and plotting through based on their inter-relationship with one another. These are all based on collecting data from multiple sources (usually other calculations behind the scenes power these overviews), and considering the feasibility of hitting these numbers given what I know about past performance, industry standards, and what the future could look like:
Example 1 – channel expectations and one key scenario switch (conv. rate)
Example 2 – emphasis on scenarios and impact on channel split
Example 3 – marketing planning for different budgets
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