For years unending, most of what organizations measured in terms of digital marketing was visibility (number of followers, likes or comments), or how brands trended on major social media platforms; howbeit, for a timeframe. While brand visibility increases the chances of converting leads to actual sales, it requires good strategy to actually achieve this, and this is the biggest task many shy away from.
Companies do exist to make profit, and 80% of all corporate problems can be resolved by increasing sales. Albeit, most corporate executives still treat digital spends as a cost center, rather than a revenue generating asset it can be, if well positioned. Digital professionals still need to justify budgets with ambiguous grammar, as Management wants to see immediate impact on the bottom line, which sometimes can be unpredictable.
Today, with the advent of Digital Analytics, it’s easier to predict the expected outcome from each marketing campaign. With a blend of analysis on user behavior and a dose of ecommerce, you can include numbers to your predictions for sales/subscriptions, etc. For example, if your company sells data subscriptions, and you find out that 50,000 users visited the sales page for 6 months, with a good understanding of user behavior, historical data and proper UI/UX tweaking, you can predict a 200% in sales if the user visits increase to say 400,000 users (this is just an estimate, can vary but using historical data sets, can be more exact).
In the last few years, this has worked for me, as I have had to build different data model sets for various marketing campaigns, in almost all sectors in this country (18 years experience is no joke 
) and I dare say it has worked more often than not.
) and I dare say it has worked more often than not.I am open to other ideas that work though, and please share.
Have a brilliant week ahead!!!
