Using Data To Improve Marketing ROI
When it comes to data and analytics, the first ‘port of call’ is often attribution, understanding in black and white which channels are converting in order to focus time, effort and money. There are however other analytics techniques which can increase marketing ROI, often with less effort. Here’s five techniques which aim to maximising digital marketing’s long term value.
LTV over CPA
Cost Per Acquisition refers to the amount of marketing or advertising money spent to convert or acquire leads. Reducing CPA is often seen a low-hanging fruit in improving ROI and controlling cost.
Companies spent a lot of time optimising landing pages, creating content, inputting negative keywords, improving their quality score, narrowing their keywords etc, and while this will help reduce the overall cost, it only factors in the initial value of the customer.
For example, if you have two campaigns A and B optimising towards signups, with CPA at £8 and £10 respectively. Campaign A appears to be a winner but what if B brings in higher quality users that spend double the amount? CPA optimisation fails to capture customers’ lifetime value (LTV) and therefore leads to suboptimal ROI.
By factoring in LTV, you are able to narrow your focus to the customers who will bring in the biggest profit to your business over a longer period of time. They may actually cost more to acquire, but the ROI will be worth it. To optimise towards LTV, you need to shift towards behavioural based metrics. This requires a more sophisticated analytics setup as these events are not triggered by simple actions and cannot easily be captured with standard tracking — a user does not click on a button that says his LTV is £100.
In order to get an overview on your marketing ROI, you need to combine data from your customer journey touchpoints (PPC, website, social media, third parties) your backend systems (sales, ERP, finance) with your behavioural data. (CRM, user logs) By centralising all of this data in an analytics warehouse, you can then apply your unique business logic to it and get a better understanding of your end-to-end customer journey and ultimate return on investment. This can then be broken down to whichever level you desire (e.g. channel, campaign, adset, creative, geo, etc) as long as you ensure the relevant information is passed to your system.
By processing data in this way, conversions will be deduplicated across platforms which will also save you money (Clients typically save 20% of ad costs when we do this) and it will also help advertisers be better prepared for the cookieless world. Google has recently announced that they will stop supporting 3rd party tracking (which powers a lot of current web tracking methodologies) in the next year. This will further widen the measurement gaps created by walled gardens and so web advertisers will seriously need to rethink digital tracking in order to keep some performance visibility across channels. In a world where there is no perfect solution and cross-channel visibility is constantly undermined by ever red lines, consolidating attribution on the advertiser’s side is a good step to protect ROI.
While greater visibility on ROI is great, revenue typically takes time to build, e.g. a user could have a subscription for years. Your marketing team optimises on-the-fly and cannot wait that long.To provide quick feedback on long term ROI, build a data science model to predict your target metrics, e.g. LTV or retention. For example, we have built LTV prediction models based on users’ first 24 hours of activity, allowing the marketing team to optimise towards long term ROI within one day from conversion! You can also pass predictions as events back to your marketing platforms (i.e. Google, Facebook, etc.) to allow their algorithms to optimise towards long term value.
Every advertising platform (Google, Facebook, etc) has sophisticated algorithms to optimise your campaign, but this doesn’t mean you can simply set something running and leave it! Staying on top of marketing campaigns requires 24/7 vigilance and sometimes in the midst of a busy campaign, it can be difficult to understand what action to take. At scale, analysing data for the latter can be very time consuming. This is when automated recommendations come in extremely handy! They support your team by providing automated cross-channel / campaign budget shift recommendations, and much more. This is especially powerful if you have complex optimisation targets.
For example, if you are a dating app and optimise towards ROI, you might end up acquiring a lot of male users, as male users are more likely to pay. Therefore, you need to balance your ROI target with a health metric such as % female acquired by modelling any deficiencies into monetary values so campaigns can be compared like-for-like. In addition your algorithm can optimise whilst ensuring the overall % female of your marketing activity is over a preset floor.
Algorithms can crunch the data in any way as defined by your business. You can then visualise the algorithm’s recommendations in your reporting tool such as Looker or Tableau. Your digital team can then come in on Mondays already knowing what optimisation to implement.
Once you have designed your recommendation algorithms, you will have pretty much created an entity that could buy on its own. If you wish to completely automate your digital marketing buying effort, you can start passing back those recommendations to the platforms (i.e. Google, Facebook, etc.) and let the algorithms run the show! For example, your algorithms could automatically upweight or downweight specific campaigns, change bids etc.
This is it! All the above stages should help in your journey towards higher long-term marketing returns. Our team at 173Tech has worked on many projects implementing the above and we typically observe an increase of ROI by over 50% in the first month following release. Do not hesitate to reach out if you want to know more!
How 173tech can help
If you want to apply data to your marketing an optimise return on investment, we can help. Our team is friendly and always happy to talk through your business challenges, data set-up and growth plans.