Trigger or event data is used widely in B2B marketing to identify events within a business environment that can lead to a reaction such as a trigger to buy. These reactions – or triggers – could include seasonal factors or information relating to business relocation, new contacts employed, office opening or other business events.
Used correctly, trigger data can enable businesses to gain a more complete view and understanding of its customers and prospects. With a more in-depth knowledge of customers’ behaviour, marketers can put in place the most appropriate marketing strategies to hit the business/decision maker at the most appropriate time with an individually targeted and more relevant message.
Hitting customers and prospects at the right time, with the right message leads to an increase in marketing responsiveness, including uplift in response and retention rates. Trigger data can be found using real, derived and modelled data sources, including proprietary sources gathered from teleresearch or traditional B2B data sources such as Companies House information, or directory data. The important factor is ensuring that the data you are using is updated as often as it realistically can be. And, wherever possible, you utilise multiple sources of data in order to generate inputs that are genuinely valuable to your business. The key here is quality data input and also accurate data processing – how you match, and combine data sources and apply flags to your customer database is critical.
By combining real data sources with derived data, and applying intelligence it is now possible to provide marketers with a live feed that can not only flag changes within their customer portfolio, but also identify the best prospects to target with new offers.
Challenges
Historically, real business events such as moving office premises, new start-up businesses and the change of incumbents within key decision maker roles, have acted as triggers for marketing activity. Yet, the difficulty often lies in the fact that that there is rarely enough data, readily available to categorically identify these events quickly or even predict them in some instances.
Near’ real-time processing
Key changes can be identified in your database, as long as you are looking for them. To help with this, you need to run routines that will identify new contacts at key clients/prospects. These may often appear as new contacts rather than replacements. In either case, the change is the most important fact.
Monitor buying patterns, any sudden change in volumes of usage or supply, either up or down can provide a vital insight. Only experience will tell you what strategies to apply.
In all cases you have to ensure that your processes to identify a trigger must be regular and consistent. For example, if you use a model to predict the next best action to take, you must factor in any changes that you make to your algorithm, before blasting the whole base as if a change has taken place. All is not lost, however, if you do not have a slick, regular process. If need be hot data’ can by-pass any clunky or irregular process and go straight to the point of action. Examples would be complaint data into a service centre which should result in an immediate response.
Customers as individuals
Decision makers are individuals in their own right expect communications to be tailored to them.
As customers become savvier and their ability to switch suppliers becomes easier, it is clear that marketers should become more sophisticated in their use of data. By providing customers with competitive and appropriate products in a proactive manner at a time that makes sense to them, we are returning to the fundamentals of marketing best practice.
In this environment trigger data is an essential tool in any marketing strategy. Identifying key events in the lifecycle of a business such as moving office, or new contacts within a customer or prospect organisation represent an opportunity for marketers to prove to the customer that they know and understand them, but without being intrusive.
Trigger data for prospecting
Equally the application of database management to the challenge of prospecting is another way in which triggers can help identify and secure new business. Identifying new start-up businesses and the main contacts within them is a sure fire way of putting your business on the radar of potentially lucrative new customers.
Trigger data for retention
Using trigger data for retention may seem an unusual approach as historically trigger data has been used more for prospecting. However, the use of trigger data for retention can be very cost-effective.
It is not enough to react to a lapsed customer when they tell you they are lapsing, or moving to another supplier. It is much more effective to proactively approach the customer and offer them an alternative at a point when they are open to offers from your organisation. Behaviour patterns must be evaluated for signals indicating loss of interest or interest displaced by a competitor. Keeping a track of buying patterns and product usage is vital in this case.
Ensure that there is a feedback mechanism from the sales order system into the CRM (Customer Relationship Management) system. Associated with this must be the compelling proposition required to keep the customer. It is not good enough to say to the sales team “give the guy a call – it looks like he is going to defect.” By then, it will be too late.
Armed with the trigger information you can immediately put marketing retention campaigns into action, offering your customer the best possible deals for their needs in order to retain their business. Using trigger data to retain customers offers a unique value proposition. Marketers no longer have to guess that a purchasing decision might’ be made. They know that purchasing decisions are imminent. The key is to use fresh data. Even data that is weeks old, undermines the whole concept of marketing to trigger events.
Sustained approach
The use of trigger data is most effective when it not just considered a one off, but an ongoing strategy for both prospecting and retention.
It is possible to monitor your portfolio on an ongoing basis to react to the triggers – the ongoing management of your portfolio will ensure that you do not miss any opportunities that present themselves.
Your database can be used as the basis for retention activity such as the provision of flags on a weekly basis to identify changes that would otherwise affect your business relationship. These flags should be delivered in a way that they can make the most positive impact – such as feeding directly into your customer management system in order to provide your sales team with notification of changes in their key accounts.
Use wisely
The key to the successful implementation of trigger data is its efficient development, management and deployment as part of your retention or acquisition strategies. Find a supplier or suppliers of data that are able to provide the broadest source of data on which to base your marketing decisions. Where possible look for expertise within your vertical sector, then explore the most appropriate ways in which you can match your data against the trigger information.
B2B data matching is not a straightforward process, and it may be easier to outsource this. If this is the case and you are placing your most valuable asset – your customer portfolio in external hands – then ensure that appropriate levels of non-disclosure are in place.
Central to the success of any marketing activity based on trigger data is its incorporation into the business strategy and processes. The data you will receive could have a significant positive impact on your revenues, and so it is vital that your business understands the value of the data feeds, and what action to take if they receive information on an account which they are responsible for.
The characteristics of an effective trigger data process
- Comprehensive – provides a complete view across the whole population
- Timely – data can be accessed quickly as is possible as the event occurs
- Sustainable – the data feed is future proofed
- Consistent – the data can be relied upon
- Relevant – the triggers provide forewarning or anticipation of a likely change in behaviour
