8 April 2020
Big Data & Predictive Analytics – Beyond the Buzzwords
Every business today needs one essential piece of kit: a crystal ball. If you could predict the future, risk and…
1 December 2016
If you’ve ever been to New York, it’s highly likely that you’ve eaten a hotdog on a street corner! Let’s take a minute or so to step into the shoes of the vendor who sold it to you.
Although the comparison won’t make sense from all points of view, as a hotdog seller, you have regular clients, you undertake lead-acquisition actions, you receive visits to your stand, and your clients have different tastes and preference.
I will add that you, as a hotdog seller who is technologically at the top of their game, will inevitably want to take a look at your dashboard at the end of the day. Incidentally, as your small business is increasingly thriving, you are mainly focusing on marketing actions and leaving the selling to others.
Unlike selling hotdogs, the selling of B2B products and services may be very complex. Depending on the case, you will find yourself dealing with sales that you are able to directly track from your campaign-management system, or with negotiation phases that are completely disconnected from your marketing actions.
This point makes it essential for you to have good discussions with your sales teams to ascertain what they are putting on their own dashboards. It should be possible to build bridges between your key figures and theirs.
Even more so than in B2C, the last-click (where the channel to have “touched” the client last is given credit for the sale) does not make much sense in B2B. Indeed, if we go back to our hotdog selling comparison, how do we know whether we can attribute the sale to the human billboard walking around 50 metres away from the stand, to the advertising posters your client came across or to the singular and familiar smell of the hotdogs being sold?
When there is exposure to several channels, it’s the overall contribution that has to be taken into account and measured. In the case of email, we will try to visualise the number of email openings compared with all exposure to other channels. We will try to verify, in the sales, what the volume of exposure to email is versus the average volume of exposure.
…but not necessarily linked to good performance in your sales. Email marketing is one part of your clients’ journey towards a buying decision. So you cannot restrict yourself to the analysis of their gross performances (opening rates, click-through rates, etc.). It’s important to look further and analyse, for example, the action that took place after the click-through and to integrate that into your dashboards.
If you decide to put a dashboard in place, you’re doing so for it to be read! However, it will be difficult to use the same dashboard for everyone. During its design, you should think about at least two types of public:
Your management:
It really is the “big picture” that matters here. Focus on the key figures, on their evolution and the goals you have set yourself for the year. It may also be worth highlighting the campaigns that obtained the best results. However, don’t try to provide the results for all of the campaigns undertaken; this would be the best way of ensuring that no one wants to read your dashboard.
You and the marketing teams:
A priori it will be read only by people with the keys to decipher it. Nonetheless, bear in mind that it must be used. That’s to say that, on reading it, you should be capable of drawing out opportunities to optimise your marketing programme and, above all, of measuring the effectiveness of the different improvements you’ve made in the past.
Let’s come back to our New York sidewalk. What matters to our hotdog seller is knowing what products they are going to sell to their clients. If ketchup and mustard remain the essentials, what are the performances of their different sauces? What do women like most? Does the season influence the desserts they‘re going to sell on their menus? How do they differentiate their product offering when they are set up in a business district or in front of a university?
You should also be able to find all of these questions in your dashboards. It should be possible to process your different key figures from different angles:
Types of B2B emailing:
We cannot analyse all emails in the same way; we have to distinguish between:
Temporal data:
Targets:
In B2B, many criteria can be used to segment and compare your performances. It may be extremely beneficial to enrich your dashboards with this data. It will then let you target only the most profitable profiles:
Sources of acquisition:
Whether your leads are natural (content marketing, inbound marketing) or provided by databases such as that provided by Sparklane, it’s important to analyse your results by comparing the performances by source of acquisition. This may enable you to verify the ROI of your different acquisition strategies, or at least to verify the most effective and the least effective.
RFM (Recency, Frequency and Monetary Value):
We’ve not heard the last of good old RFM. Does a recent purchase have influence on the performances of your emails? Do frequent buyers “consume” your newsletters more? Does the purchase amount over a given period have an impact on the performances of your campaigns?
What about a dashboard in “exploratory” mode? With a classic segmentation strategy, you target certain individuals depending on what you are selling. But in exploratory mode, the opposite is also possible. So, if your reporting is capable of it, you could discover certain groups that have had unexpected conversations about some of your products.
First and foremost, if you only had to retain 4 figures, it would really be two times four figures. A first series for your key figures, a second for the analysis of your campaigns.
Figures
B2B emailing campaign analysis
Here we’re obviously in a very traditional area! What is worth analysing in addition is the same data in the different dimensions referenced above.
In conclusion, it’s important to keep in mind that a dashboard is read at a glance. This glance should help you immediately detect an anomaly, a significant change in trends. Only then will you go into the details so as to attempt to find out what event led to this change. Don’t make the mistake of starting the other way around!