Account Based Intelligence: Should We Rely On Predictions?
The era of “spray and pray” has thankfully come to an end and with it the understanding that the sales funnel needs a new shape. Marketing and sales strategies require a refocus with an emphasis on quality versus volume. Account Based Intelligence (ABI) is the paradigm shift touted to be the agent of transformation between businesses and their future customers. But what will be the most effective approach – predictive analytics or fact based intent? Perhaps a combination? The conversation is yielding polarized viewpoints with many marketers still unaware of the differences.
We have seen the evolution of the concept of the buying team. The numbers of individuals involved in major B2B purchases is increasing. We now have numerous stakeholders and we need to know how to target the right roles in each organization. A shift to Account Based Intelligence (ABI) makes it easier to work with sales leaders to know what kinds of accounts should be targeted, and having the knowledge necessary to target individuals. ABI equips the salesperson with the right content for any buyer.
Marketers and sales reps have always sought a level of personal relationship with customers to ensure sales. A major stumbling block to resonating with customers has been a lack of small data –understanding who each person is on the buying team and what they care about (ie,personas). This required massive amounts of data and intelligence and we welcomed workflow automation. The huge amount of information generated was perhaps only helpful if you were focusing on the right potential customers from the outset.
Account Based Intelligence means carefully identifying a set of target accounts that will be marketed to in a highly personalized way. Essentially identifying the ideal prospect, and having the intelligence about that prospect, that will drive higher sales.
Why hasn’t everyone immediately embraced Account Based Marketing?
- Some relationship-focused marketers worried that the approach seemed too forced and impersonal.
- It was seemingly impossible to select target accounts for ABM in a data-driven way due to the incomplete nature of data in CRM’s and MAT’s.
- The lists of potential targets were too extensive and the information could not always reliably predict an accurate conversion rate to actual customers. Until now…
Adopting Account Based Intelligence requires a total rethink of traditional marketing methods. You are not just working on a new tech platform or engaging a different marketing activity you are rewiring your marketing strategy thinking completely. You have to refashion everything. Campaigns will have to be fundamentally changed, content re-imagined and you might need to let go of your traditional audiences in favor of the new. This is scary territory for companies with an entrenched marketing strategy.
The Popular Choice
There is an unprecedented amount of data thanks to CRM and MAT technology systems which has changed the B2B landscape. Marketers are increasing turning towards ABM initiatives to identify target accounts and key decision makers. As the ABM popularity explosion continues we are witness to the rise of another trend –predicative analytics.
Predictive analytics claims to identify and prioritize accounts, to sell the right products with the right messages.
This ensures that the enormous ocean of data has now shrunk to a manageable pond of the most promising opportunities. Marketers can get laser sharp penetration into their target accounts if they are able to send consistent and relevant messaging through a variety of channels. This success is based on predictive analytics software that enhances their ABM initiatives. Lead management and CRM provider – Chase Shiels, 4 ME Group CEO and Co-founder calls it, “the ability to target with precision.”
The analysis of patterns of attributes and signals can locate prospects beyond what your CRM are likely to convert.
Is predictive analytics really the answer?
Where predictive analytics seems to be falling short is finding B2B prospect contacts at the beginning of their buying journey. Predictive analytics will only identify look-a-like contacts. These are similar to those already in CRM based on statistical modeling.
This has led to a rising interest in time-based actions rather than predictions. Also, predictive analytics is expensive requiring a combination of existing data sources and continual database maintenance. It a lengthy period of twelve to eighteen months of fine tuning with the ROI difficult to determine at the end of the day.
There’s an alternative: Fact based analytics
Fact based Analytics sees the use of big data leveraged from the cloud in near real time that can deliver B2B prospect contacts immediately.
It is a winning combination of timeliness and certainty that ignites the call to action. These contacts are not necessarily in the CRM or marketing funnel but are those beginning their buying journey. You are able to reach out during the crucial decision-making cycle — with account based intelligence — to influence potential customers.
Predictive Analytics Vs Fact Based Intent
Predictive analysis promises the ultimate prize, delivering predictive insight in a neatly wrapped bow. Predictive analytics forecasts the future. It looks into the crystal ball of mined data to predict potential demand so businesses can act upon the generated leads. It delivers a statistical model of future customer behavior based on historical data. We know what happened in the past and so we can learn from it to predict what will happen in the near future.
With the advent of easier-to-use software predictive analytics has migrated out of the statisticians purvey and into the Marketer’s office. This has led to organizations getting a competitive advantage. In this way they are able to attract profitable customers with the knowledge of how to retain them going forward.
But it is a little like forecasting the weather? Sometimes it is actually accurate.
With fact-based data the focus switches to what is happening right now, not about what could happen in the future. Brian Giese, CEO of True Influence®, says fact-based data is like the 6 o’clock news, predictive analysis –Nostradamus. You can take instant action when there’s definite information on events as they take place. This gives you the critical head start to deliver relevant messaging in a highly specified way. There is no prediction. Only facts. The customer intent can now be conveyed to the right people in the company.
Fact-based analytics empowers businesses with the self-service opportunity of “DaaS” (Data-as-a-Service). Customers leverage the hardware of their service provider via “SaaS” – utilizing its expertise for automating data science. The laymen business becomes the data scientist without major IT involvement.
Fact versus Fiction
Customers and prospects are leaving data footprints everywhere and Intent Signaling Data (ISD) is a key part in gauging all aspects of the different “shoes.” Tons of data trails are being mined from the internet and public forums as well as internal databases so that marketers can access and utilize this essential marketer resource. While it appears that fact based intent and predictive analytics produce the same results there is a clear difference and the difference is TIME. There is a definitive move towards fact based intent as it gives you time-based action without the wait. Those able to tap this Account Based Intelligence resource are going to come out on top.